Data warehouse uye Enterprise Resource Planning | DWH uye ERP

ARCHIVE DATA CENTRAL : HISTORY ED EVOLUTION

Iwo maviri madingindira ehunyanzvi hwemakambani muma90 aive i deta rekuchengeta uye ERP. Kwenguva yakareba hova mbiri idzi dzine simba dzave zvikamu zvekambani IT isina kumbove nemharadzano. Zvaiita sekunge vaive nyaya uye vanopesana nenyaya. Asi kukura kwezviitiko zvese zviri zviviri kwakatungamira mukusangana kwavo. Nhasi makambani ari kutarisana nedambudziko rekuita neERP uye deta rekuchengeta. Ichi chinyorwa chichatsanangura kuti matambudziko ndeapi uye kuti anogadziriswa sei nemakambani.

PAKUTANGA…

Pakutanga kwaivapo deta rekuchengeta. Data yekuchengetedza yakazvarwa kurwisa iyo transaction process application system. Mumazuva ekutanga kudzidzira nemusoro dati yaireva kuti ingori poindi kune transaction processing applications. Asi mazuvano kune zvakanyanya kuomarara zviono zvekuti a deta rekuchengeta. Munyika yanhasi deta rekuchengeta inoiswa mukati mechimiro chinogona kunzi Corporate Information Factory.

Iyo CORPORATE INFORMATION FACTORY (CIF)

Iyo Corporate Information Factory ine zvakajairwa zvivakwa zvezvivakwa: kodhi yekubatanidza uye shanduko layer inobatanidza i dati apo ini dati vanofamba kubva kunzvimbo yekushandisa kuenda kunharaunda ye deta rekuchengeta yekambani; a deta rekuchengeta yekambani iyo dati vanyori venhoroondo vakadzama uye vakabatanidzwa. The deta rekuchengeta yebhizinesi inoshanda sehwaro panogona kuvakirwa dzimwe nzvimbo dzese dzenharaunda deta rekuchengeta; chitoro che data chekushanda (ODS). An ODS chimiro chakasanganiswa chine chimwe chikamu che deta rekuchengeta uye zvimwe zvinhu zvenzvimbo yeOLTP; data marts, uko madhipatimendi akasiyana anogona kuve neyawo vhezheni ye deta rekuchengeta; a deta rekuchengeta kuongorora uko vanofunga nezvekambani vanogona kuendesa yavo 72-awa mibvunzo isina chinokuvadza pane deta rekuchengeta; uye yepedyo mutsara ndangariro, umo dati chembere uye dati zvakawanda zvinogona kuchengetwa pane zvakachipa.

IPI ERP INOsanganiswa neiyo CORPORATE INFORMATION FACTORY

Iyo ERP inobatana neCorporate Information Factory munzvimbo mbiri. Kunyanya seyekutanga application inopa i dati yekushandiswa kwe deta rekuchengeta. Munyaya iyi i dati, inogadzirwa seyakagadzirwa-chigadzirwa chemaitiro ekutengeserana, inosanganiswa uye inotakurwa mu deta rekuchengeta yekambani. Chechipiri chinongedzo pakati peERP neCIF iODS. Chokwadi, munzvimbo zhinji ERP inoshandiswa seyechinyakare ODS.

Kana ERP ikashandiswa sechinhu chakakosha, iyo ERP imwe chete inogona kushandiswa muCIF seODS. Chero zvazvingava, kana ERP ichizoshandiswa mumabasa ose maviri, panofanira kuva nemusiyano wakajeka pakati pezvikwata zviviri izvi. Mune mamwe mazwi, kana ERP ikaita basa rekutanga application uye ODS, masangano maviri ekuvaka anofanirwa kusiyaniswa. Kana kushandiswa kumwe chete kweERP kuyedza kuzadzisa mabasa ese ari maviri panguva imwe chete panenge paine matambudziko mukugadzira uye kuita kweiyo chimiro.

AKASIYANA ODS UYE BASIC APPLICATIONS

Pane zvikonzero zvakawanda zvinotungamirira kukupatsanurwa kwezvikamu zvekuvaka. Zvichida chinonyanya kutaura pakuparadzanisa zvikamu zvakasiyana zvezvivakwa ndezvekuti chikamu chimwe nechimwe chezvivakwa chine maonero acho. Iyo yekutanga application inoshandisa chinangwa chakasiyana pane ODS. Edza kupindirana

maonero ekutanga ekushandisa pasirese yeODS kana zvinopesana haisi nzira yakanaka yekushanda.

Naizvozvo, dambudziko rekutanga reERP muCIF nderekuona kana paine musiyano pakati pekutanga kunyorera neODS.

DATA MODELS IN CORPORATE FORMATION FACTORY

Kuti uwane kubatana pakati pezvikamu zvakasiyana zveCIF architecture, panofanira kuva nemuenzaniso we dati. Mienzaniso ye dati vanoshanda sechinongedzo pakati pezvakasiyana zvikamu zvezvivakwa zvakaita sekutanga maapplication uye ODS. Mienzaniso ye dati vanova "mepu yenzira yekuchenjera" kuti vawane chirevo chakanaka kubva kune zvakasiyana-siyana zvekuvaka zvikamu zveCIF.

Tichifambirana nepfungwa iyi, pfungwa ndeyekuti panofanirwa kuve nemhando imwe huru uye imwechete dati. Zviri pachena kuti panofanira kuva nemuenzaniso we dati kune chimwe nechimwe chezvikamu uyezve panofanira kunge paine nzira inonzwisisika inobatanidza mhando dzakasiyana. Chimwe nechimwe chikamu chezvivakwa - ODS, baseline application, deta rekuchengeta yekambani, uye zvichingodaro .. - inoda muenzaniso wayo we dati. Uye saka panofanirwa kuve netsanangudzo chaiyo yekuti mamodheru aya sei dati vanobatana pamwe chete.

MOVE I DATA YEERP IN THE DATA Imba yekuchengetedza

Kana kwakabva the dati ibasa rekutanga uye/kana ODS, kana ERP yaisa i dati nel deta rekuchengeta, kuiswa uku kunofanira kuitika panzvimbo yakaderera ye "granularity". Kungodzokorora kana kuunganidza i dati sezvavanobuda mu ERP baseline application kana ERP ODS haisi iyo chinhu chakakodzera kuita. THE dati mashoko anodiwa mu deta rekuchengeta kugadzira hwaro hweiyo DSS maitiro. Vakadaro dati ivo vachagadziridzwa zvakare nenzira dzakawanda nedata marts uye kuongorora deta rekuchengeta.

Kufamba kwe dati kubva kuERP baseline application nharaunda kuenda ku deta rekuchengeta yekambani inoitwa nenzira yakasununguka. Kufamba uku kunoitika anenge maawa makumi maviri nemana mushure mekuvandudzwa kana kusikwa muERP. Chokwadi chekuva ne "simbe" kufamba kwe dati nel deta rekuchengeta yekambani inobvumira iyo dati kubva kuERP kuenda ku "kugadzirisa". Kamwe i dati zvakachengetwa mune yekutanga application, saka unogona kufambisa zvakachengeteka dati yeERP mubhizinesi. Chimwe chinangwa chinogona kuwanikwa nekuda kwe "simbe" kufamba kwe dati ndiyo muganhu wakajeka pakati pemaitiro ekushanda neDSS. Ne "kutsanya" kufamba kwe dati mutsetse pakati peDSS nekushanda unoramba usina kujeka.

Il moviemento dei dati kubva kuODS yeERP kuenda deta rekuchengeta yekambani inoitwa nguva nenguva, kazhinji vhiki nevhiki kana pamwedzi. Muchiitiko ichi kufamba kwe dati kunobva pakudikanwa kwoku“chenesa” ekare dati vanyori venhoroondo. Sezvineiwo, iyo ODS ine i dati izvo zviri zvitsva kupfuura dati vanyori vezvakaitika kare vakawanikwa mu deta rekuchengeta.

Kufamba kwe dati nel deta rekuchengeta inenge isati yamboitwa "wholesale" (nenzira yekutengesa). Kopa tafura kubva kunzvimbo yeERP kuenda deta rekuchengeta hazvina musoro. Imwe nzira yechokwadi ndeyekufambisa yakasarudzwa mayunitsi e dati. Chete chete dati izvo zvachinja kubva pakuvandudzwa kwekupedzisira kwe deta rekuchengeta ndidzo dzinofanirwa kutamirwa mukati deta rekuchengeta. Imwe nzira yekuziva kuti ndedzipi dati zvachinja sezvo yekupedzisira update ndeye kutarisa timestamps ye dati inowanikwa munharaunda yeERP. Mugadziri anosarudza shanduko dzese dzakaitika kubva pakuvandudzwa kwekupedzisira. Imwe nzira ndeyekushandisa shanduko yekutora matekiniki dati. Nemaitiro aya matanda uye matepi ejenari anoongororwa kuti zvionekwe kuti ndeapi dati inofanira kutamiswa kubva kunharaunda yeERP kuenda kune iyo deta rekuchengeta. Aya matekiniki akanakisa sezvo matanda uye matepi ejenari anogona kuverengerwa kubva kuERP mafaera pasina imwe mhedzisiro pane zvimwe ERP zviwanikwa.

ZVIMWE ZVINOGONESA

Imwe yezvinetso zveERP muCIF ndizvo zvinoitika kune mamwe masosi ekushandisa kana ai dati yeODS yavanofanira kupa kwairi deta rekuchengeta asi ivo havasi chikamu che ERP nharaunda. Zvichipa iyo yakavharwa ye ERP, kunyanya SAP, ichiedza kubatanidza makiyi kubva kunze zvinyorwa zve dati neni dati izvo zvinobva kuERP panguva yekufamba i dati nel deta rekuchengeta, idambudziko guru. Uye ndezvipi chaizvo zvingangoitika kuti i dati yezvishandiso kana ODS kunze kweiyo ERP nharaunda ichabatanidzwa mune iyo deta rekuchengeta? Iwo mikana yakakwira chaizvo.

FIND DATA NHOROONDO KUBVA KUERP

Rimwe dambudziko ne i dati yeERP ndiko kubva pakuda kuve dati vanyori venhoroondo mukati me deta rekuchengeta. Kazhinji the deta rekuchengeta zvinodiwa dati vanyori venhoroondo. Uye ERP tekinoroji kazhinji haichengete izvi dati nhoroondo, kanenge kwete kusvika pamwero kuti zvakakodzera mu deta rekuchengeta. Apo huwandu hwakawanda hwe dati matanda anotanga kuwedzera munzvimbo yeERP, iyo nharaunda inoda kucheneswa. Somuenzaniso, ngatiti a deta rekuchengeta inofanira kutakurwa nemakore mashanu e dati nhoroondo nepo ERP ichichengeta inokwana mwedzi mitanhatu yeizvi dati. Chero bedzi kambani ichigutsikana kuunganidza huwandu hwe dati nhoroondo sezvo nguva inopfuura, saka hapana dambudziko kushandisa ERP sosi nokuda deta rekuchengeta. Asi apo deta rekuchengeta anofanira kudzokera shure nenguva uye kutora vamwari dati nhoroondo iyo isati yambounganidzwa uye kuponeswa neERP, ipapo ERP nharaunda inova isingashande.

ERP UYE METADATA

Imwe kufunga kuita nezve ERP e deta rekuchengeta ndiyo iri pane metadata iripo munharaunda yeERP. Sezvo metadata inofamba kubva kuERP nharaunda ichienda kune deta rekuchengeta, iyo metadata inofanirwa kufambiswa nenzira imwechete. Uye zvakare, iyo metadata inofanirwa kushandurwa kuita iyo fomati uye chimiro chinodiwa neiyo zvigadzirwa deta rekuchengeta. Pane musiyano mukuru pakati pekushanda metadata uye DSS metadata. Inoshanda metadata inonyanya kuitirwa mugadziri uye ye

programmer. DSS metadata iri kunyanya kumushandisi wekupedzisira. Metadata iripo mumashandisirwo eERP kana ODS inoda kushandurwa uye shanduko iyi haisi nyore uye yakatwasuka nguva dzose.

KUSVIRA ERP DATA

Kana iyo ERP inoshandiswa semupi we dati pa il deta rekuchengeta panofanira kuva nechimiro chakasimba chinofambisa i dati kubva kune ERP nharaunda kusvika kune zvakatipoteredza deta rekuchengeta. Iyo interface inofanirwa:

• ▪ zvive nyore kushandisa
• ▪ bvumira kupinda dati zve ERP
• ▪ nzwisisa zvinorehwa ne dati izvo zviri kutamiswa deta rekuchengeta
• ▪ kuziva zvipimo zveERP zvinogona kumuka kana uchiwana dati nezve ERP:
• ▪ kuvimbika
• ▪ hukama hwevakuru vakuru
• ▪ hukama hwakajeka hune musoro
• ▪ gungano rekunyorera
• ▪ zvimiro zvese zve dati inotsigirwa neERP, zvichingodaro…
• ▪ kwanisa kuwana dati, nekupa:
• ▪ kufamba kwakananga kwe dati
• ▪ kuwana shanduko dati
• ▪ tsigira kuwana nenguva dati
• ▪ kunzwisisa chimiro che dati, zvichingoenda zvakadaro… INTERFACE NESAP Iyo interface inogona kuva yemhando mbiri, yekumba kana yekutengesa. Mamwe makuru makuru ekutengeserana anosanganisira:

• ▪ SAS
• ▪ Zvishongo Zvikuru
• ▪ D2k, zvichingodaro... MULTIPLE ERP TECHNOLOGIES Kubata ERP nharaunda sekunge ingori tekinoroji iko kukanganisa kukuru. Kune akawanda ERP matekinoroji, imwe neimwe iine masimba ayo. Vanonyanya kuzivikanwa vatengesi pamusika ndeiyi:

• ▪ SAP
• ▪ Oracle Financials
• ▪ PeopleSoft
• JD Edwards
• ▪ Baans SAP SAP ndiyo yakakura uye yakazara ERP software. SAP mafomu anosanganisira akawanda marudzi ekushandisa munzvimbo dzakawanda. SAP ine mukurumbira wekuve:

• ▪ yakakura kwazvo
• ▪ zvakaoma zvikuru uye zvinodhura kushandisa
• ▪ inoda vanhu vakawanda uye vanachipangamazano kuti vaite
• ▪ inoda vanhu vane hunyanzvi hwekuita
• ▪ inoda nguva yakawanda yekushandisa Uyewo SAP ine mukurumbira wekudzidzira nemusoro dati pedyo, zvichiita kuti zvive zvakaoma kune mumwe munhu kunze kwenzvimbo yeSAP kuti azviwane. Simba reSAP nderekuti inokwanisa kutora uye kuchengetedza huwandu hukuru hwe dati. SAP ichangobva kuzivisa chinangwa chayo chekuwedzera zvikumbiro kune deta rekuchengeta. Pane zvakawanda zvakanakira uye zvakaipira kushandisa SAP semutengesi deta rekuchengeta. Kubatsira ndeyekuti SAP yakatoiswa uye vazhinji vanopa mazano vatoziva neSAP.
  Izvo zvakashata zvekuve neSAP semupi we deta rekuchengeta akawanda: SAP haina ruzivo munyika ye deta rekuchengeta Kana SAP ari mutengesi we deta rekuchengeta, zvakakosha "kubvisa" i dati kubva kuSAP kuenda deta rekuchengeta. zuva a SAP's track record yekuvhara system, hazvibviri kuva nyore kuwana i kubva kuSAP mairi (???). Kune nzvimbo dzakawanda dzenhaka dzinosimbisa SAP, dzakadai seIMS, VSAM, ADABAS, ORACLE, DB2, zvichingodaro. SAP inoomerera pane "isina kugadzirwa pano" maitiro. SAP haidi kubatana nevamwe vatengesi kuti vashandise kana kugadzira iyo deta rekuchengeta. SAP inoomerera pakugadzira iyo yega software pachayo.

Kunyangwe SAP iri kambani hombe uye ine simba, chokwadi chekuyedza kunyora zvakare tekinoroji yeELT, OLAP, system manejimendi uye kunyange nheyo yekodhi ye. dbms kupenga chete. Panzvimbo pekutora maitiro ekushandira pamwe nevashambadziri deta rekuchengeta Nenguva refu, SAP yakatevera nzira iyo "vanoziva zvakanyanya". Iyi mafungiro inobata shure kubudirira iyo SAP inogona kuva nayo munharaunda deta rekuchengeta.
Kuramba kweSAP kubvumira vatengesi vekunze kuti vawane yavo nekukasira uye nenyasha dati. Chinhu chaicho chekushandisa a deta rekuchengeta iri nyore kupinda dati. Nyaya yose yeSAP inobva pakuita kuti zvive zvakaoma kuwana dati.
Kushaikwa kweSAP yeruzivo mukubata nemavhoriyamu makuru e dati; mumunda we deta rekuchengeta kune mavhoriyamu e dati haana kumboonekwa kubva kuSAP uye kubata aya mahombe e dati iwe unofanirwa kuve neiyo tekinoroji yakakodzera. SAP sezviri pachena haizive nezveiyi tekinoroji chipingamupinyi chiripo kupinda mumunda we deta rekuchengeta.
SAP's corporate tsika: SAP yakavaka bhizinesi mukuwana i dati kubva kuhurongwa. Asi kuti uite izvi unofanira kuva nemafungiro akasiyana. Sechinyakare, makambani esoftware anga akanaka pakuwana data munzvimbo yagara asina kunaka pakuwana data kuti iende neimwe nzira. Kana SAP ichikwanisa kuita rudzi urwu rwekushandura, ichava kambani yekutanga kuita kudaro.

Muchidimbu, hazvina mubvunzo kana kambani ichifanira kusarudza SAP semupi we deta rekuchengeta. Kune njodzi dzakakomba kune rumwe rutivi uye mibayiro mishoma pane imwe. Asi pane chimwe chikonzero chinoodza mwoyo kusarudza SAP semupi deta rekuchengeta. Nokuti kambani imwe neimwe inofanira kuva yakafanana deta rekuchengeta yemamwe makambani ese? The deta rekuchengeta ndiwo mwoyo wemakwikwi. Kana kambani yese yakagamuchira zvakafanana deta rekuchengeta zvingava zvakaoma, kunyange zvisingabviri, kuwana mukana wemakwikwi. SAP inoita seinofunga kuti a deta rekuchengeta inogona kuonekwa sekiki uye ichi chimwezve chiratidzo chemafungiro avo e "tora data mukati" maapplication.

Hapana mumwe ERP mutengesi ane simba seSAP. Pasina mubvunzo pachava nemakambani achaenda nenzira yeSAP kune yavo deta rekuchengeta asi zvichida ava deta rekuchengeta SAPs ichave yakakura, inodhura, uye inopedza nguva kugadzira.

Mamiriro ezvinhu aya anosanganisira zviitiko zvakadai sekugadzirisa vatengesi vebhangi, maitiro ekuchengetedza ndege, maitiro ekunyunyuta kweinishuwarenzi, nezvimwe zvakadaro. Kuita zvirinani hurongwa hwekutengeserana, zvakanyanya kujeka kwaive kudiwa kwekuparadzanisa pakati pekuita basa neDSS (Sarudzo Yekutsigira System). Nekudaro, neHR uye masisitimu evashandi, haufe wakatarisana nemavhoriyamu makuru ekutengeserana. Uye, hongu, kana munhu achibhadharwa kana kusiya kambani iyi irekodhi yekutengeserana. Asi zvine chekuita nemamwe masisitimu, HR uye masisitimu evashandi anongove asina zvakawanda zvekutengesa. Naizvozvo, muHR uye masystem evashandi hazvisi pachena kuti pane kudiwa kweDataWarehouse. Nenzira dzakawanda masisitimu aya mubatanidzwa weDSS masisitimu.

Asi pane chimwe chinhu chinofanira kutariswa kana uchibata nedatawarehouse uye PeopleSoft. Mumadenderedzwa akawanda, i dati HR uye zviwanikwa zvemunhu ndezvechipiri kune yekutanga bhizinesi rekambani. Mazhinji emakambani ari kugadzira, kutengesa, kupa masevhisi uye zvichingodaro. HR nevashandi masisitimu anowanzo ari echipiri kune (kana kutsigira) yekambani mutsara webhizinesi. Naizvozvo, zvine hutsinye uye hazvibatsiri a deta rekuchengeta yakaparadzana yeHR uye yemunhu zviwanikwa rutsigiro.

PeopleSoft yakasiyana chaizvo neSAP mune izvi. NeSAP, zvinosungirwa kuti pane a deta rekuchengeta. NePeopleSoft, hazvisi zvese zvakajeka. Imba yekuchengetera data inosarudzika nePeopleSoft.

Chinhu chakanakisa chinogona kutaurwa kune iyo dati PeopleSoft ndiyo iyo deta rekuchengeta inogona kushandiswa kuchengetedza i dati zvine chekuita nevanhu vekare uye zviwanikwa zvevanhu. Chikonzero chechipiri nei kambani ingada kushandisa a deta rekuchengeta a

kushata kwePeopleSoft nharaunda ndeyekubvumidza kupinda uye mahara kuwana kune maturusi ekuongorora, ai dati by PeopleSoft. Asi kunze kwezvikonzero izvi, panogona kunge paine zviitiko apo zviri nani kusave nedura re data dati PeopleSoft.

Muchidimbu

Pane pfungwa dzakawanda dzine chekuita nekuvakwa kwe a deta rekuchengeta mukati meERP software.
Zvimwe zvacho ndezvi:

• ▪ Zvine musoro kuva nea deta rekuchengeta ndiani akafanana nevamwe muindasitiri?
• ▪ ERP inochinjika sei deta rekuchengeta software?
• ▪ ERP deta rekuchengeta software inogona kubata vhoriyamu ye dati iyo iri mu adeta rekuchengeta nhandare"?
• ▪ Chii chinoitwa nemutengesi weERP pamberi pezviri nyore uye zvisingadhure, zvinotora nguva, ai. dati? (chii chinonzi ERP vatengesi vanoteedzera rekodhi pakuunza isingadhuri, nenguva, nyore kuwana data?)
• ▪ Ndeipi nzwisiso yemutengesi weERP yeDSS architecture uye fekitori yeruzivo rwekambani?
• ▪ Vatengesi veERP vanonzwisisa kuti vangawana sei dati mukati mezvakatipoteredza, asi zvakare unonzwisisa nzira yekuzvitengesa kunze?
• ▪ Mutengesi weERP akavhurika sei kumidziyo yekuchengetera data?
  Zvese izvi zvinofungwa zvinofanirwa kuitwa pakusarudza pekuisa iyo deta rekuchengeta iyo ichagamuchira i dati yeERP nevamwe dati. Kazhinji, kunze kwekunge pane chikonzero chinomanikidza chekuita neimwe nzira, kuvaka kunokurudzirwa deta rekuchengeta kunze kwe ERP mutengesi nharaunda. CHITSAUKO 1 Pfupiso yeBI Organisation Key points:
  Matura eruzivo anoshanda nenzira yakapesana neyebhizinesi njere (BI) architecture:
  Tsika dzeCorporate uye IT inogona kudzikisira kubudirira kwekuvaka masangano eBI.

Tekinoroji haisisiri iyo inodzikamisa masangano eBI. Dambudziko revagadziri uye vanoronga mapurojekiti harisi rekuti tekinoroji iripo, asi kuti vanogona kunyatsoita tekinoroji iripo.

Kumakambani mazhinji a deta rekuchengeta inopfuura zvishoma pane passive dhipoziti inogovera i dati kune vashandisi vanozvida. THE dati anotorwa kubva kusource masisitimu uye anogarwa muzvivakwa zvinonangwa ne deta rekuchengeta. ini dati vanogonawo kucheneswa chero rombo. Nekudaro hapana imwe kukosha inowedzerwa kana kuunganidzwa ne dati panguva iyi.

Zvikurukuru, passive dw, pazvakanakisa, inongopa i dati yakachena uye inoshanda kune masangano evashandisi. Kugadzira ruzivo uye kunzwisisa kwekuongorora kunoenderana zvachose nevashandisi. Tichifunga kana DW (Data yekuchengetedza) kana kubudirira kuri kuzviisa pasi. Kana tikatonga kubudirira pakukwanisa kuunganidza, kubatanidza uye kuchenesa i dati corporate pahwaro hunofungidzirwa, saka hongu, iyo DW yakabudirira. Kune rumwe rutivi, kana tikatarisa kuunganidzwa, kubatanidzwa uye kushandiswa kwemashoko sangano rose, saka DW yakakundikana. DW inopa ruzivo rushoma kana kusashaya ruzivo. Nekuda kweizvozvo, vashandisi vanomanikidzwa kuita, nekudaro kugadzira silos yeruzivo. Ichi chitsauko chinopa chiono chakakwana chekudzokorora bhizinesi reBI (Business Intelligence) architecture. Isu tinotanga netsananguro yeBI tozoenda munhaurirano dzekugadzira ruzivo nekusimudzira, kusiyana nekungopa dati kune vashandisi. Hurukuro dzinobva dzatarisa pakuverenga kukosha kwekuedza kwako kweBI. Isu tinopedzisa nekutsanangura kuti IBM inogadzirisa sei sangano rako BI zvekuvaka zvinodiwa.

Architecture tsananguro ye BI sangano

Ane simba ekutengeserana-anotungamirwa eruzivo masisitimu ave kurongeka kwezuva mubhizinesi rega rega, zvinonyatso kuenzanisa nzvimbo yekutamba yemakambani pasi rese.

Kuramba tichikwikwidza, zvisinei, iko zvino kunoda masisitimu ane ongororo anogona kushandura kugona kwekambani kuwanazve nekushandisa ruzivo rwavainarwo. Aya masisitimu ekuongorora anobva mukunzwisisa kubva kuhupfumi hwe dati iripo. BI inogona kuvandudza mashandiro kune ese ruzivo mubhizinesi rese. Mabhizinesi anogona kuvandudza hukama hwevatengi-mutengesi, kuvandudza chigadzirwa uye sevhisi pundutso, kugadzira zvibvumirano zvitsva uye zviri nani, kudzora njodzi, uye pakati pezvimwe zvakawanda zvinowana zvinoderedza mari zvakanyanya. NeBI, kambani yako inozotanga kushandisa ruzivo rwevatengi sechinhu chinokwikwidza pfuma nekuda kwezvishandiso zvine zvinangwa zvemusika.

Kuve nenzira kwayo yebhizinesi kunoreva kuve nemhinduro dzakajeka kumibvunzo yakakosha senge:

• ▪ Ndeupi wedu vatengi Dzinoita kuti tiwane mari yakawanda here, kana kuti dzinoita kuti tirasikirwe nemari?
• ▪ Kunogara zvakanakisisa zvedu vatengi maererano ne chitoro/ mudura vanogarogara?
• ▪ Ndezvipi zvezvigadzirwa zvedu nemasevhisi zvinogona kutengeswa zvinobudirira uye kuna ani?
• ▪ Ndezvipi zvinhu zvinogona kutengeswa zvinobudirira uye kunaani?
• ▪ Ndeipi mushandirapamwe wekutengesa unobudirira uye nei?
• ▪ Ndedzipi nzira dzekutengesa dzinonyanya kushanda kune zvigadzirwa zvipi?
• ▪ Tinganatsiridza sei ushamwari nezvakanaka zvedu vatengi? Makambani mazhinji ane dati zvakaoma kupindura iyi mibvunzo.
  Masisitimu ekushanda anoburitsa huwandu hukuru hwechigadzirwa, mutengi, uye mutengo dati kubva kunzvimbo dzekutengesa, kuchengetedza, basa revatengi uye tekinoroji rutsigiro masisitimu. Dambudziko nderekuburitsa uye kushandisa ruzivo urwu. Makambani mazhinji anongowana purofiti kubva kuzvikamu zvidiki zvawo dati zvekuongorora zvine hungwaru.
  I dati yasara, kazhinji inosanganiswa ne i dati kuwana zvinyorwa zvekunze zvakaita semishumo yehurumende, nezvimwe zvakatengwa ruzivo, mugodhi wegoridhe wangomirira kuongororwa, uye dati ivo vanongoda kunatswa mune yeruzivo mamiriro esangano rako.

Ruzivo urwu runogona kushandiswa nenzira dzakati wandei, kubva pakugadzira hurongwa hwese hwekambani kusvika pakutaura wega nevashambadziri, kuburikidza nenzvimbo dzekufona, invoicing, Internet nezvimwe zvibodzwa. Mamiriro ebhizinesi anhasi anoraira kuti DW uye zvine chekuita neBI zvigadziriso zvinoshanduka kupfuura kumhanya echinyakare bhizinesi zvimiro. dati sezvakaita i dati atomic-level yakajairwa uye "nyeredzi/cube mapurazi".

Chinodiwa kuti urambe uchikwikwidza kusanganiswa kwechinyakare uye tekinoroji yepamusoro mukuyedza kutsigira yakafara analytic landscape.
Chekupedzisira, nharaunda yakajairwa inofanirwa kuvandudza ruzivo rwekambani yese, kuve nechokwadi chekuti zviito zvakatorwa semugumisiro weongororo yakaitwa zvinobatsira kuti munhu wese abatsirwe.

Somuenzaniso, ngatiti iwe unoisa yako pachako vatengi muzvikamu zvepamusoro kana zvishoma.
Ingave ruzivo urwu ruchigadzirwa nemuenzaniso wemugodhi kana dzimwe nzira, runofanira kuiswa muDW uye kuitwa kuti riwanikwe nemunhu wese, kuburikidza nechero chombo chekuwana, senge static report, spreadsheets, tables, kana online analytical processing (OLAP ).

Nekudaro, parizvino, yakawanda yerudzi urwu rweruzivo runoramba rwuri mumasilos dati yevanhu kana madhipatimendi ari kugadzira ongororo. Sangano rose zvaro rine zvishoma kana kuti harina kuoneka kuti rinzwisise. Chete nekusanganisa rudzi urwu rweruzivo mubhizinesi rako DW unogona kubvisa masilos eruzivo uye kusimudza nharaunda yako yeDW.
Pane zvipingaidzo zviviri zvakakura pakugadzira sangano reBI.
Kutanga, tine dambudziko resangano pacharo uye kuranga kwaro.
Kunyange isu tisingakwanise kubatsira nekuchinja kwemitemo yesangano, tinogona kubatsira kunzwisisa zvikamu zveBI yesangano, magadzirirwo ayo, uye kuti tekinoroji yeIBM inofambisa sei kusimukira kwayo.
Chechipiri chipingamupinyi chekukunda ndiko kushaikwa kweiyo yakabatanidzwa tekinoroji uye ruzivo rwenzira inodaidza iyo BI nzvimbo yese inopesana nechikamu chidiki chete.

IBM iri kupindura kune shanduko mukubatanidza tekinoroji. Ibasa rako kupa ruzivo rwekugadzira. Iyi dhizaini inofanirwa kuvandudzwa nehunyanzvi hwakasarudzika kubatanidza kusingadzoreki, kana kuti zvishoma, nehunyanzvi hunoomerera kune yakavhurika zviyero. Zvakare, manejimendi ekambani yako anofanirwa kuona kuti bhizinesi reBi rinoitwa panguva yakatarwa uye kwete iyo yekubvumidza kuvandudzwa kweruzivo silos inomuka kubva kune yekuzvishandira ajenda, kana zvinangwa.
Izvi hazvireve kuti BI nharaunda haina hanya nekuita kune zvakasiyana zvinodiwa uye zvinodiwa zvevashandisi vakasiyana; pachinzvimbo, zvinoreva kuti kuitwa kweizvo zvidikanwi zvemunhu uye zvinodiwa zvinoitirwa kubatsira kwesangano rose reBI.
Tsananguro yemavakirwo esangano reBI inogona kuwanikwa papeji 9 paMufananidzo 1.1. Mavakirwo acho anoratidza musanganiswa wakapfuma wetekinoroji nehunyanzvi.
Kubva pakuona kwechinyakare, chivakwa chinosanganisira zvinotevera zvikamu zvekuchengetedza

Atomic layer (Atomic Layer).

Iyi ndiyo hwaro, moyo weDw yese uye nekudaro yehungwaru hwekuzivisa.
I dati zvakachengetwa pano zvichachengetedza kuvimbika kwenhoroondo, mishumo ye dati uye zvinosanganisira zviyero zvakatorwa, pamwe nekucheneswa, kubatanidzwa, uye kuchengetwa uchishandisa mienzaniso yemigodhi.
Zvose zvinotevera kushandiswa kweizvi dati uye ruzivo rwakabatana runotorwa kubva kune ichi chimiro. Iyi inzvimbo yakanaka yekuchera migodhi dati uye nemishumo ine yakarongeka SQL mibvunzo

Operational warehouse ye dati kana kushuma hwaro hwe dati(Inoshanda data chitoro (ODS) kana kushuma Database.)

Ichi chimiro che dati yakanyatsogadzirirwa hunyanzvi hwekushuma.

I dati zvakachengetwa uye kutaurwa pamusoro pezvivakwa izvi zvinogona kupedzisira zvapararira muimba yekuchengetera kuburikidza nenzvimbo yekutandarira, kwainogona kushandiswa kucherechedzwa kwehunyanzvi.

Nzvimbo yekutamba.

Yekutanga kumira kwevazhinji dati inoitirwa nzvimbo yekuchengetera zvinhu ndiyo nzvimbo yesangano.
Hoyo i dati zvakabatanidzwa, zvakacheneswa uye zvinoshandurwa kuita dati purofiti iyo inozadza iyo warehouse chimiro

Date marts.

Ichi chikamu chezvivakwa chinomiririra chimiro che dati inoshandiswa zvakananga kuOLAP. Kuvapo kwedatamarts, kana i dati zvinochengetwa muhurongwa hwenyeredzi hwavanofukidza dati multidimensional munharaunda yehukama, kana mumafaira e dati midziyo inoshandiswa neiyo chaiyo OLAP tekinoroji, senge DB2 OLAP Server, haina basa.

Izvo chete zvinomanikidza ndezvekuti zvivakwa zvinofambisa kushandiswa kwe dati multidimensional.
Iyo dhizaini zvakare inosanganisira yakakosha Bi tekinoroji uye matekiniki anosiyaniswa se:

Spatial analysis

Nzvimbo imhepo yeruzivo kune muongorori uye yakakosha kupedzisa kugadzirisa. Nzvimbo inogona kumiririra ruzivo rwevanhu vanogara mune imwe nzvimbo, pamwe neruzivo rwekuti nzvimbo iyoyo iripi panyama maererano nenyika yese.

Kuti uite ongororo iyi, unofanirwa kutanga nekubatanidza ruzivo rwako kune latitudo uye longitudo coordinates. Izvi zvinodaidzwa se "geocoding" uye inofanirwa kunge iri chikamu chekubvisa, kushandura, uye kurodha maitiro (ETL) padanho reatomu reimba yako yekuchengetera.

Data mining.

Kubviswa kwe dati inobvumira makambani edu kukura nhamba ye vatengi, kufanotaura mafambiro ekutengesa uye kugonesa hukama hwehukama ne i vatengi (CRM), pakati pezvimwe zvirongwa zveBI.

Kubviswa kwe dati saka inofanira kubatanidzwa nezvimiro zve dati warehouse uye inotsigirwa nehurongwa hwekuchengetera zvinhu kuona zvese zvinobudirira uye zvine hunyanzvi mashandisiro etekinoroji uye maitiro ane hukama.

Sezvinoratidzwa muBI architecture, iyo atomiki level Dwhouse, pamwe nedatamarts, ndiyo yakanakisa sosi ye dati yekudhonza. Izvo zvivakwa zvakafanana zvinofanirwa kuve zvakare vanogamuchira mibairo yekubvisa kuti ive nechokwadi chekuwanikwa kune vakawanda vateereri.

Agents.

Kune "maajenti" akasiyana-siyana ekuongorora mutengi chero ipi zvayo senge, masisitimu ekushanda ekambani uye dw pachavo. Ava vamiririri vanogona kuve vepamberi neural network vakadzidziswa kudzidza nezve mafambiro panzvimbo yega yega, senge remangwana chigadzirwa chinodiwa zvichienderana nekutengesa kukwidziridzwa, kutonga-kwakavakirwa injini dzekuita kune dato seti yemamiriro ezvinhu, kana kunyange vamiririri vakareruka vanotaura zvisirizvo kune vatungamiriri vepamusoro. Aya maitiro anowanzo kuitika munguva chaiyo uye, saka, anofanirwa kunyatsobatanidzwa nekufamba kwemaitiro dati. Zvimiro zvese izvi zve dati, matekinoroji uye matekiniki anovimbisa kuti hauzopedza husiku uchigadzira sangano reBI yako.

Ichi chiitiko chichagadziridzwa mumatanho ekuwedzera, kune mapoinzi madiki.
Nhanho yega yega ibasa rakazvimirira repurojekiti, uye inodaidzwa sekudzokorora muBI dw yako kana chirongwa. Kudzokorodza kunogona kusanganisira kushandisa matekinoroji matsva, kutanga nehunyanzvi hutsva, kuwedzera masisitimu matsva ku dati , kurodha i dati kuwedzera, kana nekuwedzera kwekuongorora kwenzvimbo yako. Ndima iyi inokurukurwa zvakadzama muchitsauko 3.

Pamusoro pemaitiro echinyakare eDW uye maturusi eBI, pane zvimwe zvesangano rako reBI zvaunofanira kugadzira, zvakaita se:

Mutengi touchpoints (Mutengi kubata pfungwa).

Sezvinoita chero sangano remazuva ano kune akati wandei evatengi touchpoints anoratidza maitiro ekuva nechiitiko chakanaka kune chako vatengi. Kune echinyakare chiteshi sevatengesi, switchboard vanoshanda, yakananga mail, multimedia uye anodhinda kushambadzira, pamwe nemamwe chiteshi chazvino senge email newebhu, dati Zvigadzirwa zvine imwe nzvimbo yekubatana zvinofanirwa kutorwa, kutakurwa, kucheneswa, kugadziriswa uye kuzogarwa panzvimbo dati zveBI.

Mabhesi e dati kushanda uye kushamwaridzana kwevashandisi (Kushanda

databases uye nharaunda dzevashandisi).
Pakupera kwenzvimbo dzekusangana dze vatengi nheyo dzinowanikwa dati yekushandiswa kwekambani uye nharaunda dzevashandisi. THE dati dziripo dziripo dati zvechinyakare izvo zvinofanirwa kuunzwa pamwe nekubatanidzwa ne dati inoyerera kubva pakubata kunosangana neruzivo rwakakosha.

Vaongorori. (Vaongorori)

Mubatsiri wekutanga weBI nharaunda ndiye muongorori. Ndiye anobatsira kubva ikozvino kutorwa kwe dati inoshanda, yakabatanidzwa neakasiyana masosi e dati , yakawedzerwa nezvimiro zvakaita seyekuongororwa kwenzvimbo (geocoding) uye yakaunzwa muBI tekinoroji inobvumira kumigodhi, OLAP, yemberi SQL yekushuma uye geographic analysis. Iyo yekutanga interface yemuongorori kune nharaunda yekuzivisa ndeyeBI portal.

Nekudaro, muongorori haasi iye ega anobatsirwa kubva kuBI architecture.
Vatungamiri, masangano makuru evashandisi, uye kunyange nhengo, vatengesi uye i vatengi inofanirwa kuwana mabhenefiti mubhizinesi BI.

Back feed loop.

BI architecture inzvimbo yekudzidza. Hunhu hunhu hwebudiriro ndeyekubvumidza zvimiro zve dati kuti ivandudzwe neBI tekinoroji inoshandiswa uye nezviito zvemushandisi zvakatorwa. Muenzaniso ndewe mutengi zvibodzwa.

Kana dhipatimendi rekutengesa richiita muenzaniso wekumigodhi wezvibodzwa zvevatengi sekushandisa sevhisi nyowani, saka dhipatimendi rekutengesa harifanirwe kunge riri boka chete rinobatsirwa nebasa.

Panzvimbo iyoyo, kucherwa kwemhando kunofanirwa kuitwa sechikamu chechisikigo chekuyerera kwedata mukati mebhizinesi uye zvibodzwa zvevatengi zvinofanirwa kuve chikamu chakabatanidzwa chenzvimbo yeruzivo rwekuchengetedza, inoonekwa kune vese vashandisi. Bi-bI-centric IBM Suite inosanganisira DB2 UDB, DB2 OLAP Server inosanganisira inonyanya kukosha michina, inotsanangurwa mumufananidzo 1.1.

Isu tinoshandisa dhizaini sezvinoratidzwa mumufananidzo kubva mubhuku kutipa mwero wekuenderera uye kuratidza kuti chimwe nechimwe chezvigadzirwa zveBMM chinokwana sei muBI scheme.

Kupa Ruzivo Zvemukati (Kupa zvemukati ruzivo)

Kugadzira, kugadzira uye kuita yako BI nharaunda ibasa rinonetsa. Iyo dhizaini inofanirwa kumbundira zvese zvazvino uye zveramangwana bhizinesi zvinodiwa. Dhirowa yekuvaka inofanirwa kuve yakazara kuti ibatanidze mhedziso dzese dzinowanikwa panguva yekugadzira chikamu. Kuuraya kunofanirwa kuramba kwakazvipira kuchinangwa chimwe chete: kuvandudza iyo BI yekuvakisa sezvakaunzwa zviri pamutemo mudhizaini uye yakavakirwa muzvinodikanwa zvebhizinesi.

Zvakanyanya kuoma kutaura kuti chirango chichavimbisa kubudirira kwakati.
Izvi zviri nyore nekuti haugadzirise BI nharaunda kamwechete, asi mumatanho madiki nekufamba kwenguva.

Nekudaro, kuziva zvikamu zveBI zvekuvaka kwako kwakakosha nekuda kwezvikonzero zviviri: Iwe unotyaira ese anotevera ehunyanzvi ekuvaka sarudzo.
Iwe unozogona kuronga nehana kuronga kumwe kushandiswa kwetekinoroji kunyangwe ungasawana kudzokorora uchida tekinoroji kwemwedzi yakati wandei.

Kunzwisisa bhizinesi rako zvinodiwa zvakakwana kuchapesvedzera rudzi rwezvigadzirwa zvaunowana zvekuvaka kwako.
Dhizaini uye kusimudzira kwekuvaka kwako kunovimbisa kuti imba yako yekuchengetera ndeye

kwete chiitiko chisina kujairika, asi kuti yakanyatsofungwa, yakanyatsogadzirwa ad dhanzi ye art se mosaic yeakasanganiswa tekinoroji.

Dhizaina ruzivo rwemukati

Yese yekutanga dhizaini inofanirwa kutarisa uye kuona iwo makuru eBI zvikamu zvinozodiwa nenharaunda yese izvozvi uye mune ramangwana.
Kuziva zvinodiwa nebhizinesi kwakakosha.

Kunyangwe kusati kwatanga kuronga, murongi weprojekiti anogona kazhinji kuona chikamu chimwe kana zviviri pakarepo.
Chiyero chezvikamu zvinogona kudiwa kune yako dhizaini, zvisinei, haigone kuwanikwa nyore. Munguva yechikamu chekugadzira, chikamu chikuru chezvivakwa chinosunga iyo application yekuvandudza chikamu (JAD) pane tsvagiridzo yekuona bhizinesi zvinodiwa.

Dzimwe nguva izvi zvinodiwa zvinogona kupihwa kubvunza uye kushuma maturusi.
Semuyenzaniso, vashandisi vanotaura kuti kana vachida kuita otomatiki chirevo chazvino vanofanirwa kugadzira nekubatanidza mishumo miviri yazvino uye nekuwedzera maverengero anobva mukubatanidzwa kweiyo dati.
Nepo ichi chinodiwa chiri nyore, chinotsanangura chimwe chimiro chekushanda chaunofanirwa kusanganisira kana uchitenga maturusi ekubika kusangano rako.

Mugadziri anofanirawo kutevera zvimwe zvinodiwa kuti awane mufananidzo wakazara. Vashandisi vanoda kunyoresa kurondedzero iyi?
Mishumo inogadzirwa uye inotumirwa kune vakasiyana-siyana vashandisi? Unoda kuona iyi rondedzero mune kambani portal? Zvose izvi zvinodiwa chikamu chechidimbu chinodiwa chekutsiva gwaro remanyore sezvinodiwa nevashandisi. Kubatsira kwemhando idzi dzezvinodiwa ndekwekuti munhu wese, vashandisi uye vagadziri, vanoziva pfungwa yemishumo.

Kune mamwe marudzi emabhizinesi, zvisinei, atinofanira kuronga. Kana zvinodikanwa zvebhizinesi zvichitaurwa mumhando yemibvunzo yebhizinesi yehungwaru, zviri nyore kune ane ruzivo kuronga kuti aone mativi uye kuyera / chokwadi zvinodiwa.

Kana vashandisi veJAD vasingazive kutaura zvavanoda nenzira yedambudziko rebhizinesi, mugadziri anowanzo kupa mienzaniso kusvetuka-kutanga izvo zvinodiwa kuunganidza chikamu.
Iyo nyanzvi kuronga inogona kubatsira vashandisi kunzwisisa kwete chete bhizinesi rehurongwa, asiwo maitiro ekuriumba.
Zvinodiwa kuunganidza nzira inokurukurwa muchitsauko 3; nokuti ikozvino tinongoda kuratidza kudiwa kwekugadzira kune marudzi ose eBI zvinodiwa.

Dambudziko rebhizinesi rehurongwa harisi chete chinodiwa chebhizinesi, asiwo dhizaini yekugadzira. Kana iwe uchifanira kupindura mubvunzo wemultidimensional, saka unofanirwa kubata nemusoro, ratidza dati dimensional, uye kana uchida kubata nemusoro dati multidimensional, unofanirwa kusarudza kuti ndeupi rudzi rwetekinoroji kana tekinoroji yauchashandisa.

Iwe unoita yakachengetwa cube nyeredzi schema, kana zvese zviri zviviri? Sezvauri kuona, kunyangwe iri nyore bhizinesi nyaya inogona kukanganisa zvakanyanya dhizaini. Asi aya marudzi ezvido zvebhizinesi akajairwa uye hongu, zvirinani nevagadziri veprojekiti vane ruzivo uye vagadziri.

Pave paine gakava rakakwana nezve OLAP tekinoroji nerutsigiro, uye mhinduro dzakasiyana siyana dziripo. Kusvika pari zvino takabata kudiwa kwekuunza pamwe chete kunyorerwa kwakapfava nedimensional bhizinesi zvinodiwa, uye kuti izvi zvinodiwa zvinokanganisa sei sarudzo dzehunyanzvi hwekuvaka.

Asi ndezvipi zvinodikanwa zvisinganzwisisike zviri nyore nevashandisi kana timu yeDw? Iwe uchazomboda kuongororwa kwenzvimbo (analysisi spatial)?
Migodhi mienzaniso ye dati Vachava chikamu chinodiwa chenguva yako yemberi here? Ndiani anoziva?

Izvo zvakakosha kuti uzive kuti idzi mhando dzetekinoroji hadzizivikanwe neruzhinji nharaunda dzevashandisi uye nenhengo dzechikwata cheDW, muchikamu, izvi zvinogona kunge zviri nekuti dzinowanzo batwa nedzimwe dzemukati kana dzechitatu nyanzvi dzehunyanzvi. Iyo inyaya yekumucheto yematambudziko aya marudzi etekinoroji anoburitsa. Kana vashandisi vasingakwanise kutsanangura zvinodikanwa zvebhizinesi kana kuzvironga kuti vape gwara kune vanogadzira, vanogona kuenda vasingaonekwe kana, zvakanyanya, kungofuratirwa.

Zvimwe zvinonetsa zvinova kana mugadziri uye mugadziri asingakwanise kuziva mashandisirwo eimwe yeaya epamberi asi akakosha matekinoroji.
Sezvataigara tichinzwa Vagadziri vachiti, “zvakanaka, nei tisingazviise kusvikira tawana ichi chimwe chinhu? “Vanonyatsofarira zvinhu zvinokosha here, kana kuti vanongonzvenga zvavasinganzwisisi? Kunenge kuri fungidziro yekupedzisira. Ngatitii timu yako yekutengesa yataura chinodiwa chebhizinesi, sezvakataurwa muMufananidzo 1.3, sezvauri kuona, chinodiwa chinoumbwa nenzira yenyaya yebhizinesi. Musiyano uripo pakati pedambudziko iri neyakajairwa dimensional dambudziko chinhambwe. Muchiitiko ichi, timu yekutengesa inoda kuziva, pamwedzi wega wega, iyo yakazara kutengesa kubva kune zvigadzirwa, matura uye. vatengi vanogara mukati memakiromita mashanu kubva paimba yekuchengetera zvinhu kwavanotengesa.

Zvinosuruvarisa, vagadziri kana vavaki vanogona kungofuratira chikamu chepakati nekutaura, "Tine mutengi, chigadzirwa uye dati yedhipoziti. Ngatimbomirai kure kusvika kumwe kudzokororwa.

"Mhinduro isiriyo. Iyi mhando yedambudziko rebhizinesi ndeye BI. Inomiririra kunzwisisa kwakadzama kwebhizinesi redu uye nzvimbo yakasimba yekuongorora yevaongorori vedu. BI inodarika kubvunza zviri nyore kana kushuma, kana kunyange OLAP. Izvo hazvireve kuti matekinoroji aya haana kukosha kuBI yako, asi iwo ega haamiriri iyo BI nharaunda.

Dhizaini yemamiriro eruzivo (Design for Information Content)

Zvino zvataona Bhizinesi Zvinodiwa izvo zvinosiyanisa zvakasiyana-siyana zvakakosha zvikamu, zvinofanirwa kuverengerwa mune yakazara dhizaini yekuvaka. Zvimwe zvezvikamu zveBI chikamu chekuedza kwedu kwekutanga, nepo zvimwe zvisingaitwe kwemwedzi yakati wandei.

Nekudaro, zvese zvinozivikanwa zvinodiwa zvinoratidzwa mudhizaini kuitira kuti kana tichida kushandisa imwe tekinoroji, isu takagadzirira kuzviita. Chimwe chinhu pamusoro peprojekti chicharatidza mafungiro echinyakare.

Iyi seti ye dati inoshandiswa kutsigira gare gare kushandiswa kwe dati dimensional inotungamirwa nenyaya dzebhizinesi dzataona. Sezvo mamwe magwaro anogadzirwa, akadai sekuvandudzwa kweprojekiti ye dati, tichatanga nekuita senge i dati vakapararira mumhoteredzo. Takaona kukosha kwekumiririra i dati nenzira yedimensional, achizvipatsanura (maererano nezvinodiwa chaizvo) kuita data marts.

Mubvunzo unotevera kupindura ndewekuti: Aya ma data marts achavakwa sei?
Iwe unovaka nyeredzi kutsigira macube, kana macube chete, kana nyeredzi chete? (kana macube ekurudyi, kana nyeredzi chaidzo). Gadzira dhizaini yeanovimba data mart inoda atomic layer kune vese dati unowana? Bvumira yakazvimirira data mart kuwana i dati zvakananga kubva kune anoshanda masisitimu?

Ndeipi Cube Tekinoroji yauchayedza kumisikidza?

Une vamwari vakawanda dati inodiwa pakuongororwa kwedimensional kana iwe unoda macubes euto rako rekutengesa renyika pavhiki kana zvese? Iwe unovaka chinhu chine simba seDB2 OLAP Server yemari kana Cognos PowerPlay cubes yesangano rako rekutengesa kana zvese? Aya ndiwo makuru ekugadzira dhizaini sarudzo dzinozokanganisa yako BI nharaunda kuenda kumberi. Ehe, waona kudiwa kweOLAP. Zvino uchazoita sei rudzi urwu rwehunyanzvi uye tekinoroji?

Ko mamwe emhando yepamusoro tekinoroji anokanganisa sei magadzirirwo ako? Ngatifungei kuti waona kudiwa kwenzvimbo musangano rako. Zvino iwe unofanirwa kuyeuka edhisheni yekudhirowa kunyangwe iwe usingaronge kugadzira nzvimbo dzemwedzi yakati wandei. Mugadziri anofanira kugadzira nhasi zvichibva pane zvinodiwa. Fungidzira kudikanwa kwekuongorora kwenzvimbo iyo inogadzira, inochengetedza, inochengetedza, uye inopa mukana kune dati spatial. Izvi zvinofanirwa kushanda sechinhu chinomanikidza maererano nemhando yesoftware tekinoroji uye zvirevo zvepuratifomu zvaunogona kufunga parizvino. Semuenzaniso, iyo manejimendi system ye data base relational (RDBMS) yaunochengetera yako atomic layer inofanirwa kuve nerobust spatial level iripo. Izvi zvinogonesa kuita kwakanyanya paunoshandisa geometry uye zvinhu zvepamhepo mumashandisirwo ako ekuongorora. Kana RDBMS yako isingakwanise kubata iyo dati (spatial-centric) mukati, saka uchafanirwa kumisikidza a data base (spatial-centric) kunze. Izvi zvinoomesera manejimendi enyaya uye zvinokanganisa kuita kwako kwese, tisingataure mamwe matambudziko ainogadzirira maDBAs ako, sezvo vangangove nekunzwisisa kushoma kwezvakakosha. dati nzvimbo zvakare. Kune rimwe divi, kana yako RDMBS injini inobata zvese zvepasi uye optimizer yayo ichiziva izvo zvakakosha zvinodiwa (semuenzaniso, indexing) yezvinhu zvepamhepo, ipapo maDBA ako anogona nyore kubata nyaya dzekutonga uye iwe unogona kuwedzera kuita.

Zvakare, iwe unofanirwa kugadzirisa nzvimbo yekutarisa uye atomic nharaunda layer kuti ubatanidze kero yekuchenesa (a

chinhu chakakosha chekuongorora nzvimbo), pamwe nekuchengetedza kunotevera kwezvinhu zvepakati. Kutevedzana kwemadhizaini edhizaini kunoenderera ikozvino sezvo taunza pfungwa yehutsanana hwekero. Chechimwe chinhu, ichi chishandiso chinoraira rudzi rwesoftware yaunoda kune yako ETL kuedza.

Iwe unoda zvigadzirwa zvakaita seTrillium kuti zvikupe kero yakachena, kana mutengesi weETL wesarudzo yako kuti upe kushanda ikoko?
Parizvino zvakakosha kuti iwe unokoshesa mwero wekugadzira unofanirwa kupedzwa usati watanga kuchengetedza imba yako yekuchengetera. Mienzaniso iri pamusoro inofanira kuratidza kuwanda kwesarudzo dzekugadzira dzinofanirwa kutevera kuzivikanwa kwechero bhizinesi rinodiwa. Kana dzaitwa nemazvo, idzi sarudzo dzekugadzira dzinosimudzira kudyidzana pakati pezvimiro zvenzvimbo yako, sarudzo yetekinoroji inoshandiswa, uye kufambiswa kwehuwandu hwemashoko. Pasina iyi yakajairwa BI dhizaini, sangano rako richave riri pasi pemusanganiswa wakashata wetekinoroji iripo, zvakasununguka zvakarukwa pamwechete kuti ipe kugadzikana kunooneka.

Chengetedza zvinyorwa zvemashoko

Kuunza kukosha kwemashoko kusangano rako ibasa rakaoma zvikuru. Pasina kunzwisisa kwakakwana uye ruzivo, kana huinjiniya hwakakodzera uye dhizaini, kunyangwe zvikwata zvakanakisa zvingakundikana. Nekune rimwe divi, kana iwe uine huru intuition uye yakadzama dhizaini asi pasina chirango chekuita, iwe wakangopambadza mari yako nenguva nekuti kuedza kwako kunotadza kukundikana. Mharidzo inofanirwa kuve yakajeka: Kana iwe uchishaya humwe kana humwe hwehunyanzvi uhu, kunzwisisa / ruzivo kana kuronga / dhizaini kana kuita kurangwa, izvi zvinotungamira mukuremadza kana kuparadza kuvaka kweBI sangano.

Chikwata chako chakagadzirira zvakakwana here? Pane chero munhu pachikwata chako cheBI anonzwisisa yakakura yekuongorora mamiriro anowanikwa munzvimbo dzeBI, uye matekinoroji uye matekinoroji anodiwa kuchengetedza iwo mamiriro? Pane chero munhu pachikwata chako anogona kutaura mutsauko mukushandisa advanced

static reporting uye OLAP, kana mutsauko uripo pakati peROLAP neOLAP? Mumwe wenhengo dzechikwata chako anonyatsoziva nzira yemugodhi uye kuti ingakanganisa sei imba yekuchengetera zvinhu kana kuti imba yekuchengetera inogona kutsigira kuita kwemigodhi? Nhengo yechikwata inonzwisisa kukosha kwe dati nzvimbo kana agent-based technology? Iwe une mumwe munhu anokoshesa yakasarudzika maturusi application yeETL vs Message Broker tekinoroji? Kana usina, tora imwe. BI yakakura kudarika yakajairwa atomic layer, OLAP, nyeredzi schemas uye ODS.

Kuve nekunzwisisa uye ruzivo rwekuziva zvinodiwa zveBI uye mhinduro dzadzo kwakakosha pakukwanisa kwako kunyatso gadzira zvinodiwa nevashandisi uye kugadzira uye kuita mhinduro dzavo. Kana nharaunda yako yevashandisi ichinetseka kutsanangura zvinodiwa, zviri kune timu yekuchengetera zvinhu kuti ipe kunzwisisa ikoko. Asi kana timu yekuchengetera zvinhu

haazive mashandisirwo chaiwo eBI - semuenzaniso, kucherwa kwedata - saka hazvina kunaka kuti nharaunda dzeBI dzinowanzo kugumira pakuva passive repositories. Nekudaro, kufuratira tekinoroji idzi hakudzikisi kukosha kwavo uye mhedzisiro yavanove nayo pakubuda kwebhizinesi rehungwaru kugona kwesangano rako, pamwe neruzivo rwaunoronga kusimudzira.

Dhizaini inofanirwa kusanganisira pfungwa yekudhirowa, uye zvese zvinoda munhu ane hunyanzvi. Uye zvakare, kuronga kunoda timu werehouse uzivi uye kutevedzera zviyero. Semuenzaniso, kana kambani yako yakamisa chiyero chepuratifomu kana yaona imwe RDBMS yainoda kumisikidza papuratifomu, zvakakosha kuti munhu wese ari muchikwata atevedzere zviyero izvozvo. Kazhinji boka rinoratidza kudiwa kwekumisikidzwa (kunharaunda dzevashandisi), asi timu pachayo haidi kutevedzera zviyero zvakamiswa mune dzimwe nzvimbo dzekambani kana zvimwe mumakambani akafanana. Haisi hunyengeri chete, asi inosimbisa kuti kambani haigone kushandisa zviwanikwa zviripo uye mari. Hazvireve kuti hapana mamiriro ezvinhu anotendera isina-yakajairwa chikuva kana tekinoroji; zvisinei, kuedza kweimba yekuchengetera zvinhu

vanofanira kuchengetedza negodo zviyero zvebhizinesi kudzamara zvinodiwa nebhizinesi zvaraira neimwe nzira.

Chinhu chechitatu chakakosha chinodiwa kuvaka sangano reBI chirango.
Zvinoenderana zvachose, zvakaenzana pamunhu uye pane zvakatipoteredza. Vanoronga mapurojekiti, vatsigiri, vavaki, uye vashandisi vanofanirwa kuonga chirango chinodiwa kuvaka ruzivo rwekambani. Vagadziri vanofanira kutungamira kuedza kwavo kwekugadzira kuzadzisa zvimwe kuedza kunodiwa munzanga.

Semuenzaniso, ngatiti kambani yako inovaka ERP application ine chikamu chekuchengetera zvinhu.
Saka ibasa revagadziri veERP kushandirapamwe neboka renzvimbo yekuchengetera zvinhu kuitira kuti vasakwikwidzane kana kudzokorora basa ratotanga.

Kuranga inyaya zvakare inoda kutariswa nesangano rose uye inowanzogadzwa nekupihwa simba padanho repamusoro.
Vatungamiriri vanoda kutevedzera nzira yakagadzirwa here? Maitiro anovimbisa kugadzira zvemukati zveruzivo izvo zvinozopedzisira zvaunza kukosha kunzvimbo dzese dzebhizinesi, asi pamwe zvichikanganisa hurongwa hwemunhu kana wedhipatimendi? Rangarira chirevo chekuti "Kufunga nezve zvese kwakakosha pane kufunga nezve chinhu chimwe". Chirevo ichi ndechechokwadi kumasangano eBI.

Nehurombo, matura mazhinji anotarisa kuedza kwavo kunanga uye kuendesa kukosha kune rimwe dhipatimendi kana chaivo vashandisi, vasina hanya nesangano rose. Ngatitii maneja anokumbira rubatsiro kubva kuboka rewarehouse. Chikwata chinopindura nekuedza kwemazuva makumi mapfumbamwe kunosanganisira kwete chete kuendesa zviziviso zvinotsanangurwa nemukuru asi kuve nechokwadi chekuti zvese. dati base inosanganiswa muyero yeatomu isati yaunzwa mune yakarongwa cube tekinoroji.
Iyi yeinjiniya yekuwedzera inovimbisa kuti iyo warehouse bhizinesi inobatsirwa kubva kune dati inodiwa namaneja.
Nekudaro, maneja akataura kune vekunze mafemu ekubvunza akakurudzira chikumbiro chakafanana nekutumira mukati memavhiki mashoma mana.

Tichifunga kuti timu yemukati weimba inokwanisa, mukuru ane sarudzo. Ndiani anogona kutsigira iyo yekuwedzera chirango cheinjiniya inodiwa kukura iyo bhizinesi ruzivo asset kana anogona kusarudza kuvaka yavo mhinduro nekukurumidza. Iyo yekupedzisira inoita seinosarudzwa zvakanyanya uye inongoshanda kugadzira midziyo yeruzivo inobatsira vashoma kana munhu.

Zvinangwa zvenguva pfupi uye zvenguva refu

Vagadziri uye vanoronga mapurojekiti vanofanirwa kugadzira chiono chenguva refu chezvese zvivakwa uye zvirongwa zvekukura sangano reBI. Uku kusanganiswa kwekuwana kwenguva pfupi uye kuronga kwenguva refu ndiwo mativi maviri ekuedza kweBI. Short run mari ndiyo chikamu cheBI icho chine chekuita nekudzokorora kweimba yako yekuchengetera.

Apa ndipo apo vanoronga, vagadziri uye vatsigiri vanotarisa pakusangana nezvinodiwa zvebhizinesi. Iri padanho rino panovakwa zvimiro zvemuviri, tekinoroji inotengwa uye matekiniki anoitwa. Izvo hazvina kumboitwa kuti zvigadzirise zvakanangana nezvinodiwa sezvinotsanangurwa nenharaunda dzevashandisi. Zvese zvinoitwa mukati nechinangwa chekugadzirisa zvakanangana zvinodiwa zvinotsanangurwa neimwe nharaunda.
Kuronga-refu-refu, zvisinei, ndicho chimwe chikamu cheBI. Apa ndipo apo zvirongwa uye magadzirirwo akavimbisa kuti chero chimiro chemuviri chakavakwa, matekinoroji akasarudzwa uye matekiniki akaitwa akagadzirwa neziso rakananga kubhizinesi. Iko kuronga kwenguva refu kunopa kubatana kunodiwa kuve nechokwadi chekuti budiriro yakasimba inotorwa kubva kune chero pfuma yenguva pfupi inowanikwa.

Ratidza kuedza kwako kweBI

Un deta rekuchengeta pachayo haina kukosha kwekuzvarwa nayo. Mune mamwe mazwi, hapana kukosha kwemukati pakati pearehouse tekinoroji uye maitiro ekuita.

Kukosha kwekuedza kwese kwekuchengetedza kunowanikwa muzviito zvakaitwa semhedzisiro yenzvimbo yekuchengetera uye ruzivo rwemukati rwakarimwa nekufamba kwenguva. Ichi chinhu chakakosha kuti unzwisise usati wamboedza kufungidzira kukosha kwechero danho rekutanga.

Kakawanda, vagadziri vezvivakwa uye vanoronga vanoedza kushandisa kukosha kune yemuviri uye yehunyanzvi zvikamu zveimba yekuchengetera asi chokwadi kukosha kwakavakirwa mumabhizinesi maitiro ayo akabatwa zvakanaka nedura uye ruzivo rwakatorwa zvakanaka.

Pano pane dambudziko rekutanga BI: Unopembedza sei mari? Kana iyo imba yacho pachayo isina kukosha kwemukati, vanoronga mapurojekiti vanofanirwa kuongorora, kutsanangura, nekugadzirisa mabhenefiti kune avo vanhu vachashandisa imba yekuchengetera zvinhu kusimudzira mabhizinesi chaiwo kana kukosha kweruzivo rwakachengetedzwa, kana zvese zviri zviviri.

Kuomesa zvinhu, chero maitiro ebhizinesi akakanganiswa nekuedza kwekuchengetedza anogona kupa "zvakanyanya" kana "zvinyoro" mabhenefiti. Mabhenefiti akakosha anopa metric inobatika yekuyera kudzoka pakudyara (ROI) - semuenzaniso, shandura inventory imwe nguva yekuwedzera panguva yakatarwa kana yemutengo wakaderera wekutakura pane imwe neimwe kutumira. Zvakanyanya kuoma kutsanangura mabhenefiti asina kujeka, akadai sekuvandudzwa kwekuwana ruzivo, maererano nekukosha kunobatika.

Batanidza purojekiti yako kuti uzive iyo zvikumbiro zvebhizimisi

Kazhinji, varongi veprojekiti vanoedza kubatanidza kukosha kwekuchengetedza neamorphous bhizinesi zvinangwa. Nekutaura kuti "kukosha kweimba yekuchengetera zvinhu kunobva pakukwanisa kwedu kugutsa zvikumbiro zvehurongwa" tinovhura nhaurirano nenzira inofadza. Asi izvo chete hazvina kukwana kuona kana kuisa mari mudura zvine musoro. Zvakanakisa kubatanidza warehouse reps neyakajeka bhizinesi kubvunza uye manotsi.

Kuyera ROI

Kuverengera ROI munzvimbo yekuchengetera zvinhu kunogona kunyanya kuoma. Zvinonyanya kuoma kana mutungamiri

yedzokororo yakati chinhu chisingabatike kana kuti chiri nyore kuyera. Imwe ongororo yakawana kuti vashandisi vanoona iwo maviri mabhenefiti makuru eBI maitiro:

• ▪ Ita kuti vanhu vakwanise kuita zvisarudzo
• ▪ Ita kuti vanhu vawane mashoko
  Aya mabhenefiti akapfava (kana akapfava) mabhenefiti. Zviri nyore kuona kuti tingaverengera sei ROI zvichibva pane yakaoma (kana yakakura) bhenefiti senge yakaderedzwa mutengo wekutakura, asi tinoyera sei kugona kuita zvirinani sarudzo?
  Izvi zvechokwadi zvinonetsa kune vanoronga chirongwa pavanenge vachiedza kuita kuti kambani iite mari mune imwe nzvimbo yekuchengetedza. Kuwedzera kutengesa kana kuderera kwemitengo haisisiri iwo epakati madingindira anotyaira nharaunda yeBI.
  Pane kudaro, uri kutarisa kune zvikumbiro zvebhizinesi zvekuwana zvirinani ruzivo kuitira kuti rimwe dhipatimendi riite sarudzo nekukurumidza. Aya madhiraivha ehungwaru anoitika akakosha zvakaenzana kune bhizinesi asi ari kusanzwisisika uye zvakanyanya kuoma kuratidza mune inobatika metric. Muchiitiko ichi, kuverenga ROI kunogona kutsausa, kana zvisina basa.
  Vagadziri veprojekiti vanofanirwa kuratidza kukosha kunooneka kune vatariri kuti vasarudze kana iyo mari mune imwe iteration yakakosha. Nekudaro, isu hatisi kuzopa nzira nyowani yekuverenga ROI, uye isu hatizoite nharo kana kupokana nayo.
  Kune zvakawanda zvinyorwa uye mabhuku aripo anokurukura izvo zvakakosha zvekuverenga ROI. Kune yakakosha kukosha zvirevo senge kukosha pakudyara (VOI), inopihwa nemapoka akaita seGartner, yaunogona kutsvaga. Pane kudaro, isu tinozotarisa pane epakati maficha echero ROI kana zvimwe zvakakosha zvirevo zvaunoda kufunga. Kushandisa ROI Pamusoro pekupokana nezve "zvakaoma" maringe ne"zvinyoro" mabhenefiti ane chekuita neBI kuedza pane dzimwe nyaya dzekufunga kana uchishandisa ROI. Semuyenzaniso:

Kupa mari yakawandisa kuDW kuedza kwaizouya zvakadaro
Ngatitii kambani yako yatama kubva kune mainframe architecture kuenda kune yakagoverwa UNIX nharaunda. Saka chero mari inogona (kana kusagona) kuwanikwa kubva mukuedza ikoko haifanire kunzi ndeye chete, kana zvikaitika (?), kudura.

Kusaverengera zvese kunodhura. Uye kune zvinhu zvakawanda zvekufunga nezvazvo. Funga nezverunyorwa runotevera:

• ▪ Mutengo wekutanga, kusanganisira kugona.
• ▪ Mutengo wehardware yakatsaurirwa pamwe nekuchengetera kwakabatana nekutaurirana
• ▪ Mutengo wesoftware, kusanganisira manejimendi e dati uye mutengi/sevha yekuwedzera, ETL software, DSS tekinoroji, maturusi ekuona, kuronga uye mafambiro ekushanda, uye yekutarisa software, .
• ▪ Mutengo wekugadzira dhizaini dati, nekugadzirwa, uye optimization ye
• ▪ Mutengo wekuvandudza software wakanangana nekuedza kweBI
• ▪ Mutengo werutsigiro rwemba, kusanganisira kuita optimization, kusanganisira software vhezheni kutonga uye kubatsira mashandiro Isa "Big-Bang" ROI. Kuvaka imba yekuchengetera sechinhu chimwe chete, kuedza kukuru kunotadza kukundikana, saka zvakare kuverenga iyo ROI yebhizinesi hombe chirongwa Chipo chinokatyamadza, uye kuti vanoronga vanoramba vachiedza kuyedza kufungidzira kukosha kwekuedza kwese. Sei varongi vachiedza kuisa kukosha kwemari padanho rebhizinesi kana ichizivikanwa zvakanyanya uye ichigamuchirwa kuti kufungidzira kudzokororwa kwakaoma kwakaoma? Zvinokwanisika sei? Hazvibviri kunze kwezvishoma zvishoma. Usazviita. Izvozvi zvata simbisa zvekusaita kana uchiverenga ROI, heano mashoma mapoinzi achakubatsira iwe kumisikidza yakavimbika maitiro ekufungidzira kukosha kweBI yako kuedza.

Kuwana ROI mvumo. Zvisinei nesarudzo yako yehunyanzvi yekufungidzira kukosha kwekuedza kwako kweBI, inofanirwa kubvumirana nemapato ese, kusanganisira vanoronga mapurojekiti, vanotsigira, uye vatungamiriri vemakambani.

Dzvanya ROI kuita zvikamu zvinozivikanwa. Nhanho inodiwa kune inonzwisisika ROI kuverenga ndeyekutarisa iyo kuverenga pane chaiyo purojekiti. Izvi zvino zvinokutendera kuti ufungidzire kukosha kwakavakirwa pane zvakati bhizinesi zvinodiwa zvinosangana

Tsanangura mari. Sezvatotaurwa, mari yakawanda inofanirwa kutariswa. Pamusoro pezvo, mitengo haifanire kusanganisira kwete chete idzo dzine hukama neiyo iteration yemunhu asi zvakare mitengo ine chekuita nekuona kutevedzana nemaitiro ebhizinesi.

Tsanangura zvakanakira. Nekubatanidza zvakajeka ROI kune chaiyo bhizinesi zvinodiwa, isu tinofanirwa kugona kuona mabhenefiti anozotungamira mukuzadzisa zvinodiwa.

Deredza mari uye mabhenefiti mune zvave kuitika. Ndiyo nzira yakanakisa yekumisa kukosha kwako pane net ikozvino kukosha (NPV) kupesana nekuyedza kufanotaura kukosha kweramangwana mumihoro yeramangwana.

Chengetedza nguva yekuparadzanisa ROI yako kusvika padiki. Iyo yakanyatso kunyorwa mukufamba kwenguva yakashandiswa muROI yako.

Shandisa yakawanda ROI formula. Kune dzakawanda nzira dzekufanotaura ROI, uye iwe unofanirwa kuronga kushandisa imwe kana dzakawanda dzadzo, kusanganisira net ikozvino kukosha, yemukati mwero wekudzoka (IRR), uye kubhadhara.

Tsanangura nzira inodzokororwa. Izvi zvakakosha pakuverenga chero kukosha kwenguva refu. Iyo imwechete inodzokororwa maitiro inofanirwa kunyorwa kune ese anotevera mapurojekiti madiki-anoteedzana.

Matambudziko akanyorwa ndiwo anonyanya kutsanangurwa nenyanzvi dzenzvimbo yewarehouse. Kusimbirira kwemanejimendi kuendesa "Big-Bang" ROI kunovhiringa. Kana iwe ukatanga kuverenga kwako kwese kweROI nekuipwanya kuita zvinozivikanwa, zvikamu zvinobatika, une mukana wakanaka wekufungidzira fungidziro yeROI chaiyo.

Mibvunzo nezve ROI mabhenefiti

Pasinei zvapo nebetsero dzako, dzakapfava kana kuti dzakaoma, unogona kushandisa mishomanene mibvunzo inokosha kuona ukoshi hwayo. Semuyenzaniso, uchishandisa sikero yakapfava, kubva pa1 kusvika pagumi, unogona kuyera kukanganiswa kwekuedza kupi zvako uchishandisa mibvunzo inotevera:

• Ungayera sei kunzwisisa dati uchitevera chirongwa ichi chekambani yako?
• Ungayera sei kuvandudzwa kwemaitiro semugumisiro wepurojekiti iyi?
• Ungayere sei kukanganisa kweruzivo rutsva uye fungidziro dzava kuwanikwa nekudzokorora uku
• Chii chaive nemhedzisiro yenzvimbo itsva uye dziri nani dzemakombiyuta semugumisiro wezvakadzidzwa? Kana mhinduro dzemibvunzo iyi dziri shoma, zvinogoneka kuti bhizinesi harikodzeri mari yakaitwa. Mibvunzo ine zvibodzwa zvepamusoro inonongedza kukosha kwakakosha uye inofanirwa kushanda semirayiridzo yekuenderera mberi nekuongorora. Semuenzaniso, chibodzwa chepamusoro chekuvandudzwa kwemaitiro chinofanirwa kutungamira vagadziri kuti vaongorore kuti maitiro akagadziridzwa sei. Unogona kuona kuti zvimwe kana zvese zvakawanikwa zvinobatika uye nekudaro kukosha kwemari kunogona kushandiswa zviri nyore. Kuwana zvakanyanya kubva pakudzokorora kwekutanga kwe imba yekuchengetera Mubairo mukuru wekuedza kwebhizinesi rako kazhinji mune mashoma ekutanga kudzokorora. Uku kuedza kwekutanga kunogadzira ruzivo rwakakosha kune veruzhinji uye kubatsira kumisa hwaro hwetekinoroji kune inotevera BI application. Kazhinji imwe neimwe inotevera inotevera ye dati zvemapurojekiti ekuchengetera zvinhu zvinounza kushomeka uye kushoma kwekuwedzera kukosha kune bhizinesi rose. Izvi ndezvechokwadi kunyanya kana iyo iteration isingawedzere misoro mitsva kana kusangana nezvinodiwa nenharaunda yevashandisi.

Iyi ficha yekuchengeta inoshandawo kune kukura mastacks e dati vanyori venhoroondo. Sezvo kuedza kunotevera kunoda zvakawanda dati uye zvakadini dati anodururwa mudura nekufamba kwenguva, mazhinji e dati inova isinganyanyi kukosha pakuongororwa kunoshandiswa. Izvi dati vanowanzodanwa dati dzakarara uye dzinogara dzichidhura kudzichengeta nekuti hadzina kumboshandiswa.

Izvi zvinorevei kune vanotsigira chirongwa? Chaizvoizvo, vatsigiri vekutanga vanogovana kupfuura mari yekudyara. Izvi ndizvo zvekutanga nekuti ndizvo zvinokurudzira kuti pave neyakakura tekinoroji uye zviwanikwa zvenzvimbo, kusanganisira organic.

Asi aya matanho ekutanga anotakura kukosha kukuru uye saka vanoronga mapurojekiti vanowanzo fanirwa kururamisa mari.
Mapurojekiti akaitwa mushure mekuita kwako kweBI anogona kunge aine yakaderera (ichienzaniswa neyekutanga) uye yakananga mutengo, asi inounza kushoma kukosha kune bhizinesi.

Uye varidzi vesangano vanofanirwa kutanga kufunga kukanda iyo kuvaka dati uye mashoma akakodzera matekinoroji.

Data Mining: Kubvisa Dati

Zvizhinji zvezvivakwa zvezvivakwa zvinoda misiyano yedata migodhi tekinoroji uye matekiniki-
semuenzaniso, "vamiririri" vakasiyana vekuongorora pfungwa dzekufarira dze vatengi, masisitimu ekushanda kwekambani uye yedw imwechete. Ava vamiririri vanogona kunge vari advanced neural network vakadzidziswa pamapoto mafambiro, senge remangwana chigadzirwa chinodiwa zvichibva pakushambadzira kwekutengesa; mitemo-yakavakirwa injini dzekuita kune seti dato yemamiriro ezvinhu, semuenzaniso, kuongororwa kwekurapa uye kurudziro yekurapa; kana kunyange vamiririri vakareruka vane basa rekuzivisa kunze kune vatungamiri vepamusoro. Kazhinji aya maitiro ekubvisa dati si

simbisa munguva chaiyo; saka, dzinofanirwa kubatanidzwa zvizere nekufamba kwe dati ivo pachavo.

Online Analytic Processing Processing

Online analytics

Iko kugona kucheka, dhayi, kukungurusa, kudhirowa pasi uye kuita ongororo
chii-kana, chiri mukati mechikamu, chiyero cheiyo IBM tekinoroji suite. Semuenzaniso, online analytical processing (OLAP) mabasa aripo eDB2 ayo anounza dimensional ongororo muinjini ye Database zvakafanana .

Mabasa anowedzera dimensional utility kuSQL uchikohwa zvese zvakanaka zvekuve chikamu chechisikigo cheDB2. Mumwe muenzaniso wekubatanidzwa kweOLAP ndeye mudziyo wekudhonza, DB2 OLAP Analyzer Server. Iyi tekinoroji inobvumira DB2 OLAP Server cubes kuti ikurumidze uye iongororwe otomatiki kuti iwane uye itaure nezve kukosha kwe. dati zvisina kujairika kana zvisingatarisirwi kune chero cube kune wekutengesa muongorori. Uye pakupedzisira, mabasa eDW Center anopa nzira yevanovaka kuti vatarise, pakati pezvimwe zvinhu, chimiro cheDB2 OLAP cube server seyakasikwa chikamu cheETL maitiro.

Spatial Analysis Spatial analysis

Space inomiririra hafu yeanalytical anchors (conductions) inodiwa pane panorama
yakafara analytical (nguva inomiririra imwe hafu). Iyo atomiki-mwero weimba yekuchengetera, inomiririrwa muMufananidzo 1.1, inosanganisira nheyo dzenguva nenzvimbo. Nguva zvitambi anchor inoongorora nenguva uye kero ruzivo anchor inoongorora nenzvimbo. Timestamps inoitisa ongororo nenguva, uye ruzivo rwekero runoitisa ongororo nenzvimbo. Dhiagiramu inoratidza geocoding- maitiro ekushandura kero kune mapoinzi pamepu kana mapoinzi ari muchadenga kuitira kuti pfungwa dzakaita sechinhambwe uye mukati/kunze dzigone kushandiswa mukuongorora-kunoitwa padanho reatomu uye ongororo yenzvimbo ichiitwa kuwanikwa kumuongorori. IBM inopa kuwedzera kwenzvimbo, yakagadziridzwa neEnvironmental System Research Institute (ESRI), al Database DB2 kuitira kuti zvinhu zvepakati zvigone kuchengetedzwa seyakajairwa chikamu che Database hukama. db2

Spatial Extenders, inopawo ese maSQL ekuwedzera kutora mukana wekuongorora nzvimbo. Semuenzaniso, iyo SQL yekuwedzera yekubvunza pa
chinhambwe pakati pekero kana kuti poindi iri mukati kana kunze kwenzvimbo yakatsanangurwa yepolygonal, chiyero chekuongorora neSpatial Extender. Ona chitsauko 16 kuti uwane mamwe mashoko.

Database-Resident Zvishandiso Zvishandiso Database-Mugari

DB2 ine akawanda SQL BI-anogara maficha anobatsira mukuita kupatsanura. Izvi zvinosanganisira:

• Recursion mabasa ekuita ongororo, senge "tsvaga nzira dzese dzendege kubva San Francisco a New York".
• Analytical mabasa ekuyera, kuwanda, cube uye rollup mabasa ekufambisa mabasa anongoitika chete neOLAP tekinoroji, ikozvino yave chikamu chechisikigo cheinjini. Database
• Iko kugona kugadzira matafura ane mhedzisiro
  Vatengesi ve Database vatungamiriri vanosanganisa zvimwe zveBI maficha mu Database zvakafanana.
  Vatengesi vakuru ve data base ivo vari kusanganisa zvimwe zveBI maficha mu Database zvakafanana.
  Izvi zvinopa kuita kurinani uye mamwe maitiro ekuita eBI mhinduro.
  Iwo maficha uye mabasa eDB2 V8 anokurukurwa zvakadzama muzvitsauko zvinotevera:
  Technical Architecture uye Data Management Foundations (Chitsauko 5)

• DB2 BI Zvinokosha (Chitsauko 6)
• DB2 Materialized Query Tables (Chitsauko 7)
• DB2 OLAP Mabasa (Chitsauko 13)
• DB2 Yakakwenenzverwa BI Zvimiro neMabasa (Chitsauko 15) Simplified Data Delivery System Delivery system ye dati semplified

Iyo dhizaini inoratidzwa muMufananidzo 1.1 inosanganisira akawanda zvimiro dati zvenyama. Imwe iwarehouse ye dati kushanda. Kazhinji, ODS chinhu chakatarisana, chakabatanidzwa uye chazvino. Iwe unogona kuvaka ODS yekutsigira, semuenzaniso, hofisi yekutengesa. ODS kutengesa kwaizowedzera dati kubva kune akawanda akasiyana masisitimu asi yaizongochengeta, semuenzaniso, kutengeserana kwanhasi. Iyo ODS inogona zvakare kuvandudzwa kakawanda pazuva. Panguva imwe chete, maitiro anosundidzira i dati yakabatanidzwa mune mamwe maapplication. Ichi chimiro chakanyatsogadzirirwa kubatanidza dati zvazvino uye zvine simba uye angave angangove mumiriri wekutsigira chaiyo-nguva analytics, sekupa vamiririri vebasa vatengi ruzivo rwemutengi rwemazuva ano rwekutengesa kuburikidza nekubvisa ruzivo rwekutengesa kwekutengesa kubva mumabhuku acho pachayo. Chimwe chimiro chinoratidzwa mumufananidzo 1.1 inzvimbo yepamutemo yedw. Kwete chete iyi ndiyo nzvimbo yekuitwa kwekubatanidzwa kwakakosha, kwemhando ye dati, uye nekushandurwa kwe dati yeinouya imba yekuchengetera, asi zvakare inzvimbo yakavimbika uye yenguva pfupi yekuchengetera dati replicates inogona kushandiswa mukuongorora-nguva chaiyo. Kana ukafunga kushandisa ODS kana nzvimbo yekutandarira, imwe yeakanakisa maturusi ekuzadza izvi zvimiro dati kushandisa kwakasiyana mashandiro masosi ndeye DB2's heterogeneous distributed query. Kugona uku kunounzwa neinosarudzika DB2 chimiro chinodaidzwa kuti DB2 Relational Connect (mibvunzo chete) uye kuburikidza neDB2 DataJoiner (chigadzirwa chakasiyana chinoburitsa mubvunzo, kuisa, kugadzirisa, uye kudzima kugona kune heterogeneous akagoverwa RDBMSs).

Iyi tekinoroji inobvumira vanogadzira kuti dati kusunga dati yekugadzira ine analytical process. Haisi chete tekinoroji inogona kuchinjika kune chero yezvido zvekudzokorora zvinogona kumuka nechaiyo-nguva analytics, asi inogona zvakare kubatana kune dzakasiyana siyana. dati inonyanya kufarirwa, kusanganisira DB2, Oracle, Sybase, SQL Server, Informix nevamwe. DB2 DataJoiner inogona kushandiswa kuzadza chimiro dati zviri pamutemo senge ODS kana kunyange tafura yechigarire inomiririrwa muimba yekuchengetera yakagadzirirwa kukurumidza kudzoreredza kwekukurumidza kugadzirisa kana kutengeswa. Zvechokwadi, izvi zvivakwa pachazvo dati inogona kugarwa nekushandisa

imwe yakakosha tekinoroji yakagadzirirwa kudzokorora ye dati, IBM DataPropagator Relational. (DataPropagator chigadzirwa chakasiyana chepakati masisitimu. DB2 UNIX, Linux, Windows, uye OS/2 inosanganisira kudzokorora masevhisi e dati sechinhu chakajairika).
Imwe nzira yekufamba dati inoshanda yakatenderedza bhizinesi ndeye bhizinesi application yekubatanidza neimwe inozivikanwa semeseji broker. Iyi yakasarudzika tekinoroji inobvumira isingaenzaniswi kutonga kwekunongedza uye kufamba. dati kumativi kambani. IBM ine inonyanya kushandiswa meseji broker, MQSeries, kana shanduko yechigadzirwa inosanganisira zvinodiwa e-zvokutengeserana, IBM WebSphere MQ.
Kuti uwane imwe nhaurirano yekuti ungakwidziridza sei MQ kutsigira imba yekuchengetera uye BI nharaunda, shanya website yebhuku. Parizvino, zvakwana kutaura kuti tekinoroji iyi inzira yakanaka yekutora nekushandura (uchishandisa MQSeries Integrator) dati vakanangwa vanoshanda vakanyorerwa mhinduro dzeBI. Tekinoroji yeMQ yakasanganiswa uye kurongedzerwa muUDB V8 zvinoreva kuti mitsetse yemeseji yave kugona kubatwa sekunge matafura eDB2. Pfungwa yewelding queue meseji uye zvakasikwa zve Database hukama hunotungamira kunzvimbo ine simba yekusvitsa dati.

Zero-Latency Zero latency

Chinangwa chekupedzisira che IBM ndeye zero-latency ongororo. Sezvinotsanangurwa na
Gartner, BI system inofanirwa kukwanisa kupinza, kupinza, uye kupa ruzivo kune vanoongorora pazvinodiwa. Dambudziko, hongu, ndere nzira yekusanganisa dati yazvino uye chaiyo-nguva ine ruzivo rwakakosha rwenhoroondo, senge i dati inoenderana nemaitiro/pattern, kana yakabudiswa njere, senge profiling yemutengi.

Ruzivo rwakadaro runosanganisira, semuenzaniso, kuzivikanwa kwe vatengi njodzi yepamusoro kana yakaderera kana izvo zvigadzirwa i vatengi vangangotenga kana vatova nechizi mungoro dzavo dzekutengera.

Kuwana zero latency kunoenderana nematanho maviri akakosha:

• Mubatanidzwa wakakwana we dati izvo zvinoongororwa nemaitiro akaiswa uye nemidziyo yakagadzirwa neBI
• A delivery system ye dati inoshanda kuona kuti chaiyo-nguva analytics inowanikwa zvechokwadi Izvi zvinodikanwa zve zero latency hazvina kusiyana nezvinangwa zviviri zvakamiswa neIBM uye zvinotsanangurwa pamusoro. Kubatana kwakasimba kwe dati icho chikamu cheiyo IBM's seamless yekubatanidza chirongwa. Uye gadzira dhizaini system ye dati kushanda zvakanaka kunotsamira zvachose pane tekinoroji iripo iyo inorerutsa nzira yekuendesa dati. Nekuda kweizvozvo, zviviri zvezvitatu zveBMM zvibodzwa zvakakosha pakuzadzisa chechitatu. IBM iri kunyatso kuvandudza tekinoroji yayo kuti ive nechokwadi chekuti zero latency ndeyechokwadi yekuedza kwekuchengetedza. Summary / Synthesis Sangano rako reBI rinopa nzira yekuvaka nharaunda yako
  kakawanda. Inofanirwa kugadziridzwa kuratidza zvinodikanwa zvebhizinesi rako, zvazvino uye zveramangwana. Pasina chiono chakapamhama chekuvaka, kudzokororwa kweimba yekuchengetera zvinhu kunopfuura kuita zvisina tsarukano kwenzvimbo yepakati yekuchengetera izvo zvinoita zvishoma kugadzira bhizinesi hombe, rinodzidzisa. Chekutanga chipingamupinyi chevatungamiriri veprojekiti ndere nzira yekururamisa mari inodiwa kuti ikure sangano reBI. Nepo ROI kuverenga kwakaramba kuri musimboti wezviwanikwa zvezvinhu, zviri kuramba zvichinetsa kufanotaura chaizvo. Izvi zvakatungamira kune dzimwe nzira dzekuona kana uri kuwana kukosha kwemari yako. Kukosha pa Investment2 (VOI), semuenzaniso, inotengwa semhinduro. Izvo zvine basa kune vagadziri ve dati uye pane vanoronga mapurojekiti vanogadzira uye vanopa ruzivo kune masangano evashandisi uye kwete kungopa sevhisi dati. Pane musiyano mukuru pakati pezviviri izvi. Ruzivo chinhu chinoita mutsauko mukuita sarudzo nekubudirira; zvishoma, i dati ivo vari kuvaka matombo ekutora iwo ruzivo.

Nyangwe vachitsoropodza kwakabva dati kugadzirisa zvinodiwa nebhizinesi, iyo BI nharaunda inofanirwa kuita basa rakakura mukugadzira ruzivo rwemukati. Isu tinofanirwa kutora mamwe matanho ekuchenesa, kubatanidza, kushandura, kana neimwe nzira kugadzira zvemukati izvo vashandisi vanogona kuita pazviri, uyezve tinofanira kuona kuti izvo zviito uye sarudzo, pazvine musoro, zvinoratidzwa munzvimbo yeBI. Kana isu tikaregedzera warehouse kushanda chete dati, iva nechokwadi chokuti masangano evashandisi achagadzira zvinyorwa zvemashoko zvinodiwa kutora matanho. Izvi zvinoita kuti nharaunda yavo ikwanise kuita sarudzo dziri nani, asi bhizinesi rinotambura nekushaikwa kweruzivo rwavakashandisa. zuva kuti vanogadzira uye vanoronga mapurojekiti vanotanga mapurojekiti chaiwo munharaunda yeBI, vanoramba vachizvidavirira kune bhizinesi rose. Muenzaniso wakapfava weiyi mativi maviri mativi eBI iterations inowanikwa mune sosi dati. Zvese dati inogamuchirwa kune chaiyo zvikumbiro zvekutengesa inofanira kugarwa mukutanga atomic layer. Izvi zvinogonesa kuvandudzwa kweiyo bhizinesi ruzivo asset, pamwe nekutonga, kugadzirisa chaiyo mushandisi zvikumbiro zvinotsanangurwa muiteration.

Chii chinonzi Data Warehouse?

Data yekuchengetedza yanga iri moyo yeruzivo masisitimu ekuvaka kubva 1990 uye inotsigira maitiro eruzivo nekupa yakasimba yakabatanidzwa chikuva che dati nhoroondo inotorwa sehwaro hweongororo dzinotevera. THE deta rekuchengeta ivo vanopa nyore kubatanidzwa munyika isingaenderane application masisitimu. Data yekuchengetedza yashanduka kuita fadhi. Data yekuchengetedza kuronga nemusoro i dati zvinodiwa paruzivo uye maitiro ekuongorora pahwaro hwenguva refu yenhoroondo yenguva. Zvose izvi zvinosanganisira kuedza kukuru uye nguva dzose mukuvaka nekugadzirisa deta rekuchengeta.

Saka chii chinonzi a deta rekuchengeta? A deta rekuchengeta uye:

• ▪ pamusoro pezvidzidzo
• ▪ Integrated system
• ▪ kuchinja kwenguva
• ▪ isingachinji (haisi kukanzura)

muunganidzwa we dati inoshandiswa kutsigira zvisarudzo zvehutungamiri mukuita maitiro.
I dati yakaiswa mukati deta rekuchengeta vanowana muzviitiko zvakawanda kubva munzvimbo dzekushanda. The deta rekuchengeta inogadzirwa kubva kune imwe nzvimbo yekuchengetedza, yakaparadzana nemuviri kubva kune yese yehurongwa, iyo ine dati zvakamboshandurwa nemaapplication anoshanda paruzivo rwunobva munzvimbo yekushanda.

Tsanangudzo chaiyo yekuti a deta rekuchengeta inokodzera tsananguro yakakwana sezvo paine zvakakosha zvinokurudzira uye zviri pasi pezvinoreva zvinotsanangura maitiro eimba yekuchengetera zvinhu.

DZIDZO YECHIDZIDZO THEMATIC

Chinhu chekutanga che a deta rekuchengeta ndeyekuti yakanangana nezvidzidzo zvikuru zvekambani. Nhungamiro yemaitiro kuburikidza ne dati inosiyana neimwe nzira yemhando yepamusoro iyo inopa mafambiro ezvishandiso kune maitirwo nemabasa, nzira inonyanya kugovaniswa neakawanda easati achangoburwa manejimendi masisitimu.

Nyika yekushanda yakagadzirirwa kutenderedza zvikumbiro uye mabasa akadai sezvikwereti, savings, bankcards uye kuvimba nesangano rezvemari. Nyika yedw yakarongwa kutenderedza nyaya huru semutengi, mutengesi, chigadzirwa uye chiitiko. Kurongeka kwakatenderedza misoro kunokanganisa dhizaini nekuita kwe dati inowanikwa mudw. Chinonyanya kukosha, musoro mukuru unobata chikamu chakakosha chechimiro chakakosha.

Nyika yemashandisirwo inokanganiswa nezvose zviri zviviri dhizaini dhizaini uye dhizaini dhizaini. Nyika yedw yakatarisana chete nevhidhiyo modhi dati uye pakugadzirwa kwe Database. Dhizaini yekugadzira (mune chimiro chayo chekare) haisi chikamu cheiyo dw nharaunda.

Misiyano pakati pesarudzo yemaitiro/basa rekushandisa uye kusarudzwa kwechidzidzo kunoburitswawo semisiyano yezviri mugwaro. dati pamwero wakadzama. THE dati del dw haisanganisire i dati iyo isingazo shandiswa kugadzirisa DSS paunenge uchinyorera

kushanda oriented dati zvine i dati kukurumidza kugutsa zvinoshanda / kugadzirisa zvinodiwa izvo zvinogona kana kusave nechero kushandiswa kune DSS muongorori.
Imwe nzira yakakosha iyo inoshanda-inotungamirwa kunyorera dati zvakasiyana kubva dati yedw iri mumishumo ye dati. ini dati mashandiro anochengetedza hukama huripo pakati pematafura maviri kana anopfuura zvichienderana nemutemo webhizinesi unoshanda. THE dati yedw span chitsama chenguva uye mishumo inowanikwa mudw yakawanda. Mitemo mizhinji yekutengeserana (uye zvakafanana, mishumo yakawanda ye dati ) vanomiririrwa mustock ye dati pakati pematafura maviri kana kupfuura.

(Kuti uwane tsananguro yakadzama yekuti hukama pakati pe dati inotungamirirwa muDW, ndapota tarisa kune Tech Topic panyaya iyoyo.)
Kubva pasina imwe maonero kunze kweiyo yemusiyano wakakosha pakati pesarudzo yekushanda/maitiro ekushandisa uye sarudzo yezvidzidzo, pane musiyano mukuru pakati pemashandisirwo ehurongwa ne dati uye DW.

KUPIMISWA

Chinhu chinonyanya kukosha chenzvimbo yedw ndechekuti i dati inowanikwa mukati me dw inosanganiswa nyore. NGUVA DZOSE. PASINA ZVINHU. Icho chaicho chaicho chenzvimbo yedw ndechekuti i dati zviri mukati memiganhu yeimba yekuchengetera zvinhu zvakabatanidzwa.

Kubatanidzwa kunozviratidza munzira dzakawanda dzakasiyana-mumakonisheni anowirirana anoonekwa, mukuyerwa kwakafanana kwezvakasiyana, muzvimiro zvekodhi zvinoenderana, mune hunhu hwemuviri. dati inowirirana, zvichingodaro.

Kwemakore vagadziri vezvishandiso zvakasiyana vakaita sarudzo dzakawanda nezve magadzirirwo anofanirwa kugadzirwa. Maitiro uye ega ega magadzirirwo sarudzo dzevagadziri vezvikumbiro zvinoratidzwa munzira zana: mukusiyana kwekodha, yakakosha chimiro, hunhu hwemuviri, zvibvumirano zvekuzivikanwa, zvichingodaro. Iko kugona kwakasanganiswa kwevazhinji vanogadzira maapplication kugadzira zvisingaenderane maapplication ane ngano. Mufananidzo 3 unoburitsa mimwe misiyano yakakosha mumagadzirirwo emaapplication.

Encoding: Encode:

Vagadziri vezvishandiso vakasarudza coding yemunda - gender - munzira dzinoverengeka. Mugadziri anomiririra murume kana mukadzi se "m" uye "f". Mumwe mugadziri anomiririra murume kana mukadzi se "1" uye "0". Mumwe mugadziri anomiririra murume kana mukadzi se "x" uye "y." Mumwe mugadziri anomiririra hutano se "murume" uye "mukadzi." Hazvina basa kuti bonde rinopinda sei muDW. Iwo "M" uye "F" anogona kunge akanaka sechero chinomiririra.

Chinokosha ndechekuti chero kupi kwakabva munda wepabonde kubva, munda iwoyo unosvika muDW mune inopindirana yakabatanidzwa mamiriro. Nekuda kweizvozvo kana munda waiswa muDW kubva pachikumbiro kwawakamirirwa kunze muchimiro "M" uye "F", iyo dati inofanira kushandurirwa kuDW format.

Kuyerwa Kwehunhu: Kuyera kwe Hunhu:

Vagadziri vekushandisa vakasarudza kuyera pombi munzira dzakasiyana siyana mumakore. Zvitoro zvemugadziri i dati wepombi mumasendimita. Imwe application mugadziri anochengeta iyo dati yepombi maererano nemasendimita. Imwe application mugadziri anochengeta iyo dati yepombi mumamiriyoni cubic feet pasekondi. Uye mumwe mugadziri anochengetedza ruzivo rwepombi maererano nemayadhi. Chero kwakabva, kana ruzivo rwepombi rwasvika muDW runofanira kuyerwa nenzira imwe cheteyo.

Sezvinoratidzwa mumufananidzo 3, nyaya dzekubatanidza dzinokanganisa dzinenge dzese chikamu chepurojekiti - maitiro emuviri weiyo dati, dambudziko rekuva nemabviro anopfuura rimwe chete dati, nyaya yezvisingaenderane zvakaonekwa samples, mafomati e dati kusapindirana, zvichingodaro.

Chero chipi nechipi chekugadzirisa nharo, chigumisiro chakafanana - i dati inofanira kuchengetwa muDW nenzira yakasarudzika uye inogamuchirika pasi rose kunyangwe paine masisitimu ekushandisa chitoro i dati.

Kana muongorori weDSS akatarisa kuDW, chinotariswa nemuongorori chinofanira kunge chiri chekushandisa. dati dziri mudura.

pane kushamisika nezve kuvimbika kana kuenderana kweiyo dati.

TIME VARIANCY

Zvese i dati muDW vane chokwadi kune imwe nguva nenguva. Ichi chakakosha chimiro che dati muDW yakasiyana zvikuru ne dati inowanikwa munzvimbo yekushanda. THE dati yenzvimbo yekushanda ndeyechokwadi sepanguva yekuwana. Mune mamwe mazwi, munharaunda yekushanda kana chikwata chinowanikwa dati, zvinotarisirwa kuratidza kukosha sezvakangoita panguva yekuwana. Sei ini dati muDW dzakarurama sepane imwe nguva nenguva (kureva, kwete "ikozvino"), i dati anowanikwa muDW ndiwo “musiyano wenguva”.
Nguva yakasiyana ye dati neDW inotaurwa nezvayo munzira dzakawanda.
Nzira iri nyore ndeyokuti i dati yeDW inomiririra dati kwenguva yakareba - makore mashanu kusvika gumi. Nguva yenguva inoratidzwa yenzvimbo yekushanda ipfupi pane yazvino kukosha kusvika makumi matanhatu nemakumi mapfumbamwe.
Zvikumbiro zvinoda kushanda nemazvo uye zvinoda kuwanikwa pakugadzirisa kutengeserana zvinoda kuunza hushoma huwandu hwe dati kana vakabvumira chero mwero wekuchinja. Saka mashandisirwo ekushandisa ane nguva pfupi yekutarisa, senge odhiyo application dhizaini musoro.
Nzira yechipiri 'kusiyana kwenguva' kunoonekwa muDW iri muchimiro chakakosha. Imwe neimwe yakakosha chimiro muDW ine, zvakajeka kana zvakajeka, chinhu chenguva, senge zuva, vhiki, mwedzi, nezvimwe. Chinhu chenguva chinenge chiri pazasi pekiyi yakasungirirwa inowanikwa muDW. Pazviitiko izvi, chinhu chenguva chichavapo zvachose, senge iyo faira rese rinodhindwa pakupera kwemwedzi kana kota.
Yechitatu nzira yenguva musiyano inoratidzwa ndeyekuti i dati yeDW, yakanyoreswa nemazvo, haigone kuvandudzwa. THE dati yeDW ndeye, kune zvese zvinoshanda, nhevedzano refu yemifananidzo. Ehezve kana iyo snapshot yakatorwa zvisizvo, ipapo snapshots inogona kuchinjwa. Asi tichifunga kuti snapshots anotorwa nemazvo, haashandurwe kana angotorwa. Mune zvimwe

zviitiko zvinogona kunge zvisina tsika kana kusashanda kuti zvidhori zviri muDW zvigadziriswe. THE dati kushanda, kuve kwakarurama sepanguva yekuwana, inogona kuvandudzwa sezvinodiwa.

HAKUNA VOLATILE

Chinhu chechina chakakosha cheDW ndechekuti haina kushanduka.
Zvidzoreso, kuiswa, kudzima uye shanduko dzinoitwa nguva nenguva kunzvimbo dzekushanda pane rekodhi-ne-rekodhi. Asi the basic manipulation of the dati zvinodiwa muDW zviri nyore. Kune marudzi maviri chete ekushanda anoitika muDW - yekutanga kurodha kwe dati uye kuwana dati. Iko hakuna update ye dati (mupfungwa yakajairika yekuvandudza) muDW seyakajairika kugadzirisa mashandiro. Pane mimwe mhedzisiro ine simba kwazvo yemusiyano wekutanga pakati pekushanda kwekugadzirisa uye DW kugadzirisa. Padanho rekugadzira, kudiwa kwekuchenjerera pamusoro pekuparara hakusi chinhu muDW, sezvo kuvandudzwa kwe dati hazviitwe. Izvi zvinoreva kuti padanho remuviri redhizaini, rusununguko runogona kutorwa kuti uwedzere kuwana dati, kunyanya mukubata nemisoro yenormalization uye yepanyama denormalization. Imwe mhedzisiro yekureruka kweDW mukushanda kuri muhunyanzvi hwepasi rose hunoshandiswa kumhanyisa nharaunda yeDW. Kuve nekutsigira online rekodhi-ne-rekodhi zvidzoreso (sezvinowanzoitika pakugadziriswa kwekushanda) kunoda tekinoroji kuve nehwaro hwakaoma kwazvo pasi pekureruka kuri pachena.
Iyo tekinoroji inotsigira backup uye kudzoreredza, kutengeserana, uye kutendeseka kwedata dati uye kuona kwakafa uye kugadzirisa kwakaoma uye hakuna basa pakugadzirisa DW. Hunhu hweDW, dhizaini yekumisikidza, kubatanidzwa kwe dati mukati meDW, musiyano wenguva uye nyore kwekutonga kwe dati, zvese zvinotungamira kune zvakatipoteredza zvakanyanya, zvakasiyana zvakanyanya kubva kune yekare yekushanda nharaunda. Kunobva zvinenge zvose dati yeDW ndiyo nzvimbo yekushanda. Zviri kuyedza kufunga kuti kune yakakura redundancy ye dati pakati penzvimbo mbiri idzi.
Chokwadi maonero ekutanga ane vanhu vazhinji ndeekusadiwa kukuru dati pakati penzvimbo yekushanda uye nharaunda ye

DW kuwedzera. Kuturikira kwakadai ndekwepamusoro uye kunoratidza kusanzwisisa zviri kuitika muDW.
Zvechokwadi kune hushoma hwekuda redundancy dati pakati penzvimbo yekushanda uye i dati yeDW. Chimbofunga zvinotevera:I dati vanosefa dato kuti unochinja kubva kunharaunda yekushanda kuenda kunharaunda yeDW. Vazhinji dati havambobudi kunze kwenzvimbo yekushanda. Ndizvo chete i dati izvo zvinodikanwa kuti DSS igadziriswe tsvaga kutungamira kwavo munharaunda

▪ nguva yakatarisa dati yakasiyana zvikuru nemhoteredzo imwe neimwe. THE dati munzvimbo yekushanda ivo vakanyanya kutsva. THE dati muDW vakura zvikuru. Kubva pamaonero enguva, pane kupindirana kushoma pakati penzvimbo yekushanda neDW.

▪ DW ine dati pfupiso iyo isiri mumhoteredzo

▪ I dati vanopinda shanduko yakakosha pavanenge vachichinjira kuenda kuMufananidzo 3 inoratidza kuti mazhinji e dati dzakagadziridzwa zvakanyanya chero dzasarudzwa uye dzichiendeswa kuDW. Isa imwe nzira, yakawanda ye dati inoshandurwa panyama uye zvakanyanya sezvo ichiendeswa muDW. Kubva pakuona kwekubatanidzwa ivo havana kufanana dati kugara munzvimbo yekushanda. Tichifunga nezvezvinhu izvi, iyo redundancy ye dati pakati penzvimbo mbiri idzi chiitiko chisingawanzoitiki, chinotungamira kune isingasviki 1% redundancy pakati penzvimbo mbiri idzi. ZVINHU ZVINOGONA DWs dzine chimiro chakasiyana. Kune akasiyana mazinga epfupiso uye ruzivo runoganhura maDW.
Zvikamu zvakasiyana zveDW ndezvi:

• Metadata
• Dati mashoko azvino
• Dati yeruzivo rwekare
• Dati zvakapfupikiswa zvishoma
• Dati zvakapfupikiswa zvakanyanya

Parizvino chinonyanya kunetsa ndechekuti i dati mashoko azvino. Ndiyo inonyanya kunetseka nokuti:

• I dati Tsanangudzo yemazuva ano inoratidza zviitiko zvichangobva kuitika, izvo zvinogara zvichifadza uye
• i dati yazvino data data ine voluminous nekuti inochengetwa padanho rakaderera re granularity uye
• i dati yezvino ruzivo inongogara yakachengetwa mu disk memory, inokurumidza kuwana, asi inodhura uye yakaoma kubva I dati of details are old dati izvo zvakachengetwa pane imwe ndangariro ye mass. Inowanikwa pano neapo uye inochengetwa pamwero weruzivo unoenderana nawo dati mashoko azvino. Kunyange zvisingasungirwe kuchengetedza pane imwe nzira yekuchengetedza, nekuda kwehuwandu hukuru hwe dati yakabatana nekuwanikwa kweapo neapo kwe dati, nzvimbo yekuchengetera ye dati yezvinyorwa zvekare hazviwanzo kuchengetwa pa diski. THE dati vakapfupikiswa zvishoma ndivo dati izvo zvakanyungudutswa kubva kune yakawanikwa yakaderera nhanho yeruzivo kusvika kune yazvino nhanho yeruzivo. Iyi nhanho yeDW inenge ichigara yakachengetwa mudhisiki ndangariro. Matambudziko ekugadzira anozviratidza kune mugadziri weiyo dati mukuvakwa kwedanho iri reDW ndeiyi:

• Ndeipi unit yenguva iyo pfupiso yaitwa pamusoro
• Ndezvipi zvirimo, hunhu hunozopfupisa zvishoma zvirimo dati Chikamu chinotevera che dati inowanikwa muDW ndiyo ye dati zvakapfupikiswa zvakanyanya. THE dati zvakapfupikiswa zvakanyanya compact uye zviri nyore kuwanikwa. THE dati akapfupikiswa zvakanyanya dzimwe nguva anowanikwa munzvimbo yeDW uye mamwe makesi i dati zvakadhindwa zvakanyanya zvinowanikwa kunze kwemadziro eko tekinoroji inotambira DW. (chero zvakadaro, i dati zvakapfupikiswa zvakanyanya chikamu cheDW zvisinei nekuti ini dati vari mudzimba). Chikamu chekupedzisira cheDW ndicho chikamu chemetadata. Munzira dzakawanda metadata inogara mune imwe chiyero pane mamwe dati yeDW, nekuti metadata haina chero dato kutorwa zvakananga kubva munzvimbo yekushanda. Metadata ine basa rakakosha uye rakakosha muDW. Metadata inoshandiswa se:

• dhairekitori rekubatsira muongorori weDSS kuwana zviri muDW,
• gwara rekuita mepu dati kuti sei i dati dzakashandurwa kubva kunharaunda yekushanda kuenda kunharaunda yeDW,
• gwara kune algorithms inoshandiswa pakupfupisa pakati i dati mashoko azvino ei dati zvakapfupikiswa zvishoma, i dati yakapfupikiswa zvakanyanya, Metadata inoita basa rakakura zvakanyanya munharaunda yeDW kupfuura zvayakambomboita munzvimbo yekushanda. AKARE ZVINOGONA KUCHENGA ZVAKARE Magnetic tepi inogona kushandiswa kuchengeta rudzi rwakadaro dati. Chokwadi kune akasiyana siyana ekuchengetedza midhiya anofanirwa kutariswa kuchengetedza zvekare dati of details. Zvichienderana nehuwandu hwe dati, kuwanda kwekuwana, mutengo wezvishandiso uye rudzi rwekuwana, zvinogoneka zvachose kuti mamwe maturusi achada nhanho yekare yeruzivo muDW. KUFAMBA KWEDATA Kune zvakajairika uye zvinofanotaurwa kuyerera kweiyo dati mukati meDW.
  I dati vanopinda muDW kubva munzvimbo yekushanda. (Cherechedza: Pane zvimwe zvinofadza zvakasarudzika pamutemo uyu. Zvisineyi, dzinenge dzese dati pinda muDW kubva munzvimbo yekushanda). zuva kuti i dati vanopinda muDW kubva munzvimbo yekushanda, inoshandurwa sezvinotsanangurwa pamusoro apa. Chero ukapinda muDW, i dati pinda nhanho yazvino yeruzivo, sezvakaratidzwa. Inogara ipapo uye inoshandiswa kusvikira chimwe chezviitiko zvitatu chikaitika:

• wacheneswa,
• inopfupikiswa, uye/kana ▪Iyo Nzira isingachashandi mukati meDW inofamba i dati mashoko azvino a dati yeruzivo rwekare, zvichienderana nezera re dati. Maitiro

muchidimbu inoshandisa tsanangudzo ye dati kuverenga the dati zvakapfupikiswa zvishoma uye zvakapfupikiswa zvakanyanya mazinga e dati. Pane zvimwe zvinosiya kuyerera kunoratidzwa (kuzokurukurwa gare gare). Zvisinei, kazhinji, nokuda kwevakawanda zvikuru dati inowanikwa mukati meDW, rwizi rwe dati inomiririrwa.

KUSHANDISA DATAWAREHOUSE

Hazvishamisi kuti mazinga akasiyana-siyana e dati mukati meDW havagamuchire mazinga akasiyana ekushandiswa. Sezvo mutemo, iyo yakakwirira yezinga rekupfupisa, iyo yakawanda i dati vanoshandiswa.
Kushandiswa kwakawanda kunoitika mumhepo dati zvakapfupikiswa zvakanyanya, nepo zvekare dati of details anenge asingambo shandiswe. Pane chikonzero chakanaka chekuchinja sangano kune paradigm yekushandisa zviwanikwa. Zvimwe zvakapfupikiswa i dati, iyo inokurumidza uye inoshanda zvakanyanya kusvika dati. Kana a chitoro inoona kuti inoita yakawanda-yepamusoro-nhanho kugadzirisa kweDW, ipapo huwandu hukuru hwemakina zviwanikwa hunopedzwa. Zviri mufaro dzemunhu wese kuti agadzirise mwero wepamusoro wepfupiso nekukurumidza.

Kune zvitoro zvakawanda, muongorori weDSS mune pre-DW nharaunda akashandisa dati pamwero weruzivo. Munzira dzakawanda kusvika pa dati zvakadzama zvinotaridzika segumbeze rekuchengetedza, kunyangwe mamwe mazinga ekupfupisa aripo. Imwe yemabasa emugadziri we dati Kurumura mushandisi weDSS kubva pakushandisa nguva dzose dati padanho rakaderera reruzivo. Pane zviviri zvinokurudzira zviripo kune architect's dati:

• kuisa a chargeback system, uko mushandisi wekupedzisira anobhadhara zviwanikwa zvakadyiwa e
• izvo zvinoratidza kuti nguva yakanaka yekupindura inogona kuwanikwa kana maitiro ne i dati iri padanho repamusoro rekupfupisa, nepo nguva yekupindura isina kunaka ichibva pane maitiro e dati pamwero wakaderera we ZVIMWE ZVINONYANYA Kune mamwe mashoma eDW kuvaka uye manejimendi kufunga.
  Yekutanga kutariswa ndeye iyo indices. THE dati pamazinga epamusoro ekupfupisa anogona kunyoreswa zvakasununguka, nepo i dati

pamazinga akaderera eruzivo iwo akakura zvekuti anogona kunyoreswa zvishoma. Kubva pachiratidzo chimwe chete, i dati pamazinga akakwirira ezveruzivo anogona kugadziridzwa zviri nyore, nepo vhoriyamu ye dati pamazinga ezasi yakakura zvekuti i dati hazvigoni kuvandudzwa nyore nyore. Naizvozvo, iyo modhi ye dati uye basa rakarongeka rakaitwa nedhizaini rinoisa hwaro hweDW hunoshandiswa zvakada kusvika padanho razvino reruzivo. Mune mamwe mazwi, zviitiko zvekuenzanisira zve dati hazvishande kumatanho ekupfupisa, mune dzinenge nyaya dzese. Imwe fungidziro yezvimiro ndeyekugovaniswa kwe dati neDW.

Kupatsanura kunogona kuitwa pamatanho maviri - pamwero we dbms uye pamwero wekushandisa. Mukupatsanura pamwero dbmsiye dbms inoziviswa nezvezvikamu uye inoatonga zvinoenderana. Panyaya yechikamu-chikamu chechikamu, mugadziri chete ndiye anoziva kupatsanurwa uye basa rekutonga kwavo rakasiiwa kwaari.

Below level dbms, basa rakawanda rinoitwa zvoga. Pane zvakawanda zvekusachinja-chinja zvine chekuita nekuzvitonga kwemapoka. Panyaya ye division-level application ye dati Del deta rekuchengeta, basa rakawanda rinowira pamugadziri, asi mhedzisiro ndeyekuchinjika mukutonga kwe dati nel deta rekuchengeta

ZVIMWE ANOMALIES

Nepo zvikamu zve deta rekuchengeta shanda sezvakatsanangurwa kune vanenge vese dati, pane zvimwe zvinobatsira zvisiri izvo zvinoda kukurukurwa. Imwe kunze ndeye dati zvipfupiso zveruzhinji (public summary data). Izvi ndizvo dati pfupiso dzakaverengerwa kunze kwe deta rekuchengeta asi dzinoshandiswa nenzanga. THE dati zvipfupiso zveveruzhinji zvinochengetwa uye zvinotungamirwa mu deta rekuchengeta, kunyange sezvataurwa pamusoro apa ivo vanoonekwa. MaAccountant anoshanda kugadzira kota iyi dati semari inowanikwa, mari yemwedzi mitatu, purofiti yekota, zvichingodaro. Basa rinoitwa neakaundendi riri kunze kune deta rekuchengeta. Zvisinei, i dati anoshandiswa "mukati" mukati mekambani - kubva Marketing, kutengesa, nezvimwewo. Imwe inomaly, iyo isingazokurukurwa, ndeye dati external.

Imwe mhando yakatanhamara ye dati iyo inowanikwa mu a deta rekuchengeta ndiyo iyo yekusingaperi data data. Izvi zvinokonzeresa kudikanwa kwekuchengeta zvachose dati pamwero wakadzama wezvikonzero zvetsika kana zvemutemo. Kana kambani iri kufumura vashandi vayo kuzvinhu zvine njodzi pane kudiwa kwayo dati zvakadzama uye zvachose. Kana kambani ikagadzira chigadzirwa chinosanganisira kuchengetedzwa kwevanhu, sezvikamu zvendege, pane kudikanwa dati mashoko echigarire, uyewo kana kambani ikapinda muzvibvumirano zvine ngozi.

Iyo kambani haigone kufuratira iyo nhoroondo nekuti mumakore mashoma anotevera, kana paine mhosva, yeuka, kupokana kwekuvaka kukanganisa, nezvimwe. kuratidzwa kwekambani kunogona kunge kwakakura. Somugumisiro kune rudzi rwakasiyana rwe dati inozivikanwa sechigarire data data.

SUMMARY

Un deta rekuchengeta chinhu chakanangana nechinhu, chakabatanidzwa, musiyano wenguva, muunganidzwa we dati kusiri-kusagadzikana mukutsigira kwekuita sarudzo zvido zvehutungamiriri. Rimwe nerimwe remabasa akakosha a deta rekuchengeta zvine zvazvinoreva. Mukuwedzera kune mana mazinga e dati Del deta rekuchengeta:

• Old details
• Current details
• Dati zvakapfupikiswa zvishoma
• Dati yakapfupikiswa zvakanyanya Metadata zvakare chikamu chakakosha cheiyo deta rekuchengeta. ABSTRACT Pfungwa yekuchengetwa kwe dati ichangobva kugamuchira kutariswa kwakawanda uye yave chimiro che 90s. Izvi zvinokonzerwa nekugona kwe deta rekuchengeta kukurira zvipingamupinyi zvemasisitimu ekutsigira manejimendi senge sarudzo dzekutsigira masisitimu (DSS) uye Executive information masisitimu (EIS). Kunyangwe iyo pfungwa ye deta rekuchengeta zvinotaridzika zvinovimbisa, shandisa i deta rekuchengeta inogona kunetsa nekuda kwematanho makuru ekuchengetera zvinhu. Pasinei nekuoma kwemapurojekiti ekuchengetedza zvinhu zve dati, vatengesi vazhinji uye vanopa mazano vanotenga dati kupokana kuti kuchengetwa kwe dati hapana dambudziko. Zvakadaro, pakutanga kwechirongwa ichi chekutsvagisa, hapana tsvakiridzo yakazvimirira, yakasimba uye yakarongeka yakanga yaitwa. Nekuda kweizvozvo zvakaoma kutaura, chii chaizvo chinoitika muindasitiri kana ichivakwa deta rekuchengeta. Ichi chidzidzo chakaongorora tsika yekuchengetera zvinhu ye dati vemazuva ano izvo zvinovavarira kukudziridza kunzwisisa kwakapfuma kwemaitiro eAustralia. Ongororo yemabhuku yakapa mamiriro uye hwaro hwechidzidzo cheempirical. Pane zvakawanda zvakabuda kubva mutsvakurudzo iyi. Chekutanga, chidzidzo ichi chakaratidza zviitiko zvakaitika panguva yekuvandudzwa kweiyo deta rekuchengeta. Munzvimbo dzakawanda, i dati vakaungana vakasimbisa tsika yakataurwa mumabhuku. Chechipiri, matambudziko uye matambudziko anogona kukanganisa kuvandudzwa kweiyo deta rekuchengeta vakaonekwa nechidzidzo ichi. Pakupedzisira, mabhenefiti akawanikwa nemasangano eAustralia ane chekuita nekushandiswa kwe deta rekuchengeta zvaratidzwa.

Chitsauko 1

Tsvaga mamiriro

Pfungwa yekuchengetera data yakawana kufumurwa kwakapararira uye ikava maitiro ari kubuda muma90 (McFadden 1996, TDWI 1996, Shah naMilstein 1997, Shanks et al. 1997, Eckerson 1998, Adelman and Oates 2000). Izvi zvinogona kuoneka kubva kunhamba iri kukura yezvinyorwa zvekuchengetedza data mumabhuku ekutengeserana (Little and Gibson 1999). Zvinyorwa zvakawanda (ona, semuenzaniso, Fisher 1995, Hackathorn 1995, Morris 1995a, Bramblett naKing 1996, Graham et al. 1996, Sakaguchi naFrolick 1996, Alvarez 1997, Brousell 1997, 1997, Don 1997, 1997 1998. Edwards 1999, TDWI XNUMX) vakashuma zvakakosha kumasangano anoita deta rekuchengeta. Vakatsigira dzidziso yavo neanecdotal humbowo hwekuita kwakabudirira, kudzoka kwakanyanya pakudyara (ROI) nhamba, uye, zvakare, nekupa nhungamiro kana nzira dzekuvandudza. deta rekuchengeta

(Shanks et al. 1997, Seddon naBenjamin 1998, Little naGibson 1999). Mune imwe nyaya yakanyanyisa, Graham et al. (1996) yakashuma avhareji yekudzoka pamakore matatu ekudyara kwe401%.

Zvizhinji zvezvinyorwa zvemazuva ano, zvisinei, zvakakanganwa kuoma kunowanikwa mukuita zvirongwa zvakadaro. Mapurojekiti e deta rekuchengeta dzinowanzova dzakaoma uye dzakakura uye saka dzinotakura mukana mukuru wekukundikana kana dzisina kunyatsodzorwa (Shah and Milstein 1997, Eckerson 1997, Foley 1997b, Zimmer 1997, Bort 1998, Gibbs and Clymer 1998, Rao 1998). Vanoda huwandu hukuru hwevanhu uye mari zviwanikwa, nguva uye kushanda nesimba kuzvivaka (Hill 1998, Crofts 1998). Nguva yenguva nemari inodiwa ingangoita makore maviri nemamiriyoni maviri kusvika matatu emadhora, zvichiteerana (Braly 1995, Foley 1997b, Bort 1998, Humphries et al. 1999). Ino nguva uye nzira dzemari dzinodiwa kudzora nekubatanidza zvakawanda zvakasiyana-siyana zvekuchengetedza data (Cafasso 1995, Hill 1998). Padivi peiyo hardware uye software kufunga, mamwe mabasa, ayo anosiyana kubva pakubviswa kwe dati kune kurodha maitiro e dati, iyo ndangariro kugona kubata zvigadziriso uye meta dati yekudzidziswa kwemushandisi, inofanirwa kutariswa.

Panguva yakatanga chirongwa chetsvakiridzo ichi, pakanga paine tsvakiridzo shoma yefundo yaiitwa mundima yekuchengetera data, kunyanya muAustralia. Izvi zvakaonekwa kubva mukushomeka kwezvinyorwa zvakaburitswa pamusoro pekuchengetwa kwedata nemagazini kana zvimwe zvinyorwa zvedzidzo zvenguva iyoyo. Zvizhinji zvezvinyorwa zvedzidzo zviripo zvinotsanangura chiitiko cheUS. Kushaikwa kwekutsvagisa kwedzidzo munzvimbo yekuchengetera data kwakonzera kudiwa kwekutsvaga kwakasimba uye zvidzidzo zvesimba (McFadden 1996, Shanks et al. 1997, Little naGibson 1999). Kunyanya, zvidzidzo zvekutsvaga pamusoro pekuita maitiro e deta rekuchengeta zvinoda kuitwa kuwedzera ruzivo rwakakwana nezvekushandiswa kwe deta rekuchengeta uye ichashanda sehwaro hwetsvakiridzo yeramangwana (Shanks et al. 1997, Little and Gibson 1999).

Chinangwa chechidzidzo ichi, nokudaro, ndechekuongorora kuti chii chinonyatsoitika kana masangano akaita nekushandisa i deta rekuchengeta muAustralia. Kunyanya, chidzidzo ichi chichabatanidza ongororo yehurongwa hwese hwekugadzira a deta rekuchengeta, kutanga nekutanga uye dhizaini kuburikidza nekugadzira nekuita uye kushandiswa kunotevera mukati memasangano eAustralia. Mukuwedzera, chidzidzo chacho chichabatsirawo kune maitiro ezvino kuburikidza nekuona nzvimbo iyo maitiro anogona kuwedzera kuvandudzwa uye kusakosha uye njodzi dzinogona kuderedzwa kana kudziviswa. Uyezve, ichashanda sehwaro hwezvimwe zvidzidzo pa deta rekuchengeta muAustralia uye ichazadza gaka riripo parizvino mumabhuku.

Mibvunzo yokutsvakurudza

Chinangwa chetsvakiridzo iyi ndechekudzidza zviitiko zvinosanganisirwa mukuitwa kwe deta rekuchengeta uye kushandiswa kwavo nemasangano eAustralia. Kunyanya, zvinhu zvine chekuita nekuronga kweprojekiti, kusimudzira, kushanda, kushandiswa uye njodzi dzinobatanidzwa zvinodzidzwa. Saka mubvunzo weongororo iyi ndewekuti:

“Maitiro azvino uno ari sei deta rekuchengeta kuAustralia?"

Kuti upindure mubvunzo uyu zvinobudirira, inoverengeka yemibvunzo yekutsvagisa inodiwa. Kunyanya, mibvunzo midiki mitatu yakaonekwa kubva mumabhuku, ayo anoratidzwa muchitsauko 2, kutungamira chirongwa ichi chekutsvaga: deta rekuchengeta nemasangano eAustralia? Ndeapi matambudziko anowanikwa?

Ndezvipi zvikomborero zvinowanikwa?
Mukupindura mibvunzo iyi, dhizaini yekutsvagisa yekuongorora inoshandisa ongororo yakashandiswa. Sechidzidzo chekuongorora, mhinduro dzemibvunzo iri pamusoro hadzina kukwana (Shanks et al. 1993, Denscombe 1998). Muchiitiko ichi, mamwe matatu matatu anodiwa kuvandudza mhinduro dzemibvunzo iyi. Nekudaro, kuferefeta kuchapa hwaro hwakasimba hwebasa remangwana rekuongorora iyi mibvunzo. Hurukuro yakadzama yekururamisa nzira yekutsvagisa uye dhizaini inoratidzwa muchitsauko 3.

Chimiro chepurojekiti yekutsvaga

Iyi purojekiti yekutsvagisa yakakamurwa kuita zvikamu zviviri: chidzidzo chemukati cheiyo data warehousing pfungwa uye empirical research (ona Mufananidzo 1.1), imwe neimwe inokurukurwa pazasi.

Chikamu I: Chidzidzo chemamiriro ezvinhu

Chikamu chekutanga chetsvagurudzo chaive nekuongororwa kwezvinyorwa zvazvino pamhando dzakasiyana dzekuchengetera data dzinosanganisira sarudzo dzekutsigira masisitimu (DSS), Executive information masisitimu (EIS), kesi zvidzidzo zve. deta rekuchengeta uye pfungwa dze deta rekuchengeta. Zvakare, mhedzisiro yemaforamu pa deta rekuchengeta uye mapoka emisangano yenyanzvi nenyanzvi anotungamirwa neboka reMonash DSS rekutsvagisa, vakabatsira pachikamu ichi chekudzidza icho chaiitirwa kuwana ruzivo rwekuita deta rekuchengeta uye kuona njodzi dziripo pakutorwa kwavo. Munguva iyi yezvidzidzo zvemamiriro ezvinhu, kunzwisiswa kwenzvimbo yedambudziko kwakasimbiswa kuti ipe hwaro hweruzivo rwekuzotevera kuferefeta. Zvisinei, iyi yakanga iri nzira inoenderera mberi sezvo tsvakurudzo yetsvakurudzo yakaitwa.

Chikamu II: Empirical research

Iyo pfungwa nyowani yekuchengetera data, kunyanya muAustralia, yakagadzira kudiwa kweongororo kuti uwane mufananidzo wakafara wechiitiko chekushandisa. Ichi chikamu chakaitwa apo dambudziko redunhu rakange ramiswa kuburikidza nekuongorora kwakadzama kwemabhuku. Pfungwa yekuchengetera dhata yakaumbwa mukati mechikamu chechidzidzo chakashandiswa sechipo chemibvunzo yekutanga yechidzidzo ichi. Mushure meizvi, mubvunzo webvunzo wakaongororwa. Iwe uri nyanzvi pa deta rekuchengeta akapinda mubvunzo. Chinangwa chekuyedza gwaro remibvunzo yekutanga chaive chekutarisa kukwana nekururama kwemibvunzo. Kubva pane zvabuda mubvunzo, gwaro remibvunzo rakagadziridzwa uye shanduro yakagadziridzwa yakatumirwa kuvatori veongororo. Mibvunzo yakadzoswa yakazoongororwa kuti i dati mumatafura, madhayagiramu, uye mamwe mafomati. THE

ongororo zvabuda zve dati gadzira mufananidzo we data warehousing maitiro muAustralia.

DATA WAREHOUSSING ONGORORO

Pfungwa yekuchengetera data yakashanduka nekuvandudzwa kwehunyanzvi hwekombuta.
Yakanangana nekukunda matambudziko anosangana nemapoka ekutsigira maapplication akadai seDecision Support System (DSS) uye Executive Information System (EIS).

Munguva yakapfuura chipingamupinyi chikuru chezvikumbiro izvi kwave kusakwanisa kwezvikumbiro izvi kupa a data base zvinodiwa pakuongorora.
Izvi zvinonyanya kukonzerwa nemhando yebasa revatungamiri. Zvido zvehutungamiriri hwekambani zvinosiyana nguva dzose zvichienderana nenzvimbo yakavharwa. Naizvozvo i dati zvakakosha kune izvi zvikumbiro zvinofanirwa kuchinja nekukurumidza zvichienderana nechikamu chinorapwa.
Izvi zvinoreva kuti i dati inofanira kuwanikwa mufomu yakakodzera yekuongorora kunodiwa. Muchokwadi, mapoka ekutsigira maapplication akawana zvakanyanya kuoma munguva yakapfuura kuunganidza nekubatanidza dati kubva kwakaoma uye kwakasiyana-siyana.

Iyo yasara yechikamu ichi inopa tarisiro yepfungwa yekuchengetera data uye inokurukura kuti sei deta rekuchengeta inogona kukunda matambudziko emapoka ekutsigira maapplication.
Izwi rekuti “Dhata Warehouseyakakurumbira naWilliam Inmon muna 1990. Tsanangudzo yake inowanzotaurwa inoona Dhata Warehouse semuunganidzwa we dati yakanangana nezvidzidzo, yakabatanidzwa, isingaite, uye inoshanduka nekufamba kwenguva, mukutsigira sarudzo dzehutungamiriri.

Achishandisa tsananguro iyi Inmon anonongedza kuti i dati anogara mu a deta rekuchengeta anofanira kunge aine zvinotevera 4 maitiro:

• ▪ Chidzidzo chacho
• ▪ Yakabatanidzwa
• ▪ Haisi kushanduka
• ▪ Shanduko nekufamba kwenguva Nechidzidzo cheInmon zvinoreva kuti i dati nel deta rekuchengeta munzvimbo huru dzesangano dzave dziri

inotsanangurwa mumuenzaniso dati. Somuenzaniso zvose dati maererano i vatengi zvirimo munzvimbo yezvidzidzo vatengi. Saizvozvowo vose dati zvine chekuita nezvigadzirwa zvirimo muchikamu chezvidzidzo PRODUCTS.

Ne Integrated Inmon zvinoreva kuti i dati kubva kumapuratifomu akasiyana, masisitimu nenzvimbo zvinosanganiswa uye kuchengetwa munzvimbo imwechete. Sezvineiwo dati zvakafanana zvinofanirwa kushandurwa kuita mafomati anowirirana kuitira kuti zviwedzerwe nekuenzaniswa zviri nyore.
Semuyenzaniso, chirume nechikadzi chinomiririrwa nemabhii M naF mune imwe hurongwa, uye na1 na0 mune imwe. Kuti uzvibatanidze zvakanaka, imwe kana ese mafomati anofanira kushandurwa kuitira kuti mafomati maviri aenzane. Muchiitiko ichi tinogona kuchinja M kuenda ku1 uye F kuenda ku0 kana zvinopesana. Nyaya-yakatarisana uye Yakabatanidzwa inoratidza kuti iyo deta rekuchengeta yakagadzirirwa kupa chiono chinoshanda uye chinochinjika che dati nekambani.

NekuNon-volatile anoreva kuti i dati nel deta rekuchengeta ramba uchienderana uye kugadzirisa kwe dati hazvidiwi. Pane kudaro, chero shanduko mu dati yepakutanga inowedzerwa kune Database Del deta rekuchengeta. Izvi zvinoreva kuti munyori wenhoroondo we dati iri mu deta rekuchengeta.

Kune Variables nenguva Inmon inoratidza kuti i dati nel deta rekuchengeta nguva dzose iine tempo zviratidzo ei dati vanowanzoyambuka imwe nguva. Somuenzaniso a
deta rekuchengeta inogona kuve ne5 makore enhoroondo tsika dze vatengi kubva 1993 kusvika 1997. Kuwanikwa kwenhoroondo uye yenguva yakatevedzana ye dati inokubvumira kuongorora maitiro.

Un deta rekuchengeta anogona kuunganidza zvake dati kubva kuOLTP masisitimu; kubva kwaakabva dati kunze kwesangano uye/kana nemamwe akakosha ekuteya system mapurojekiti dati.
I dati zvinyorwa zvinogona kupfuura nenzira yekuchenesa, munyaya iyi i dati inoshandurwa uye yakabatanidzwa isati yachengetwa mu Database Del deta rekuchengeta. Zvadaro, i dati

kugara mukati me Database Del deta rekuchengeta anoitwa kuti awanikwe kune yekupedzisira-mushandisi logins uye yekudzoreredza maturusi. Uchishandisa zvishandiso izvi mushandisi wekupedzisira anogona kuwana iyo yakabatanidzwa yekuona kwesangano re dati.

I dati kugara mukati me Database Del deta rekuchengeta iwo anochengetwa mune zvese zvakadzama uye pfupiso mafomati.
Chiyero chechidimbu chinogona kuenderana nemhando ye dati. ini dati zvakadzama zvinogona kusanganisira dati ikozvino uye dati vanyori venhoroondo
I dati real haina kubatanidzwa mu deta rekuchengeta kusvika i dati nel deta rekuchengeta inovandudzwa zvakare.
Pamusoro pekuchengeta dati ivo, a deta rekuchengeta inogona zvakare kuchengeta rudzi rwakasiyana rwe dato inonzi METADATA inotsanangura i dati kugara mumba make Database.
Kune mhando mbiri dzemetadata: metadata yekuvandudza uye metadata yekuongorora.
Kuvandudza metadata inoshandiswa kubata uye kugadzirisa maitiro ekubvisa, kuchenesa, kugadzira mepu uye kurodha dati nel deta rekuchengeta.
Irwo ruzivo rwuri mumetadata yekusimudzira inogona kuve neruzivo rwemashandisirwo masisitimu, ruzivo rwezvinhu zvichabviswa, modhi. dati Del deta rekuchengeta uye mitemo yebhizimisi yekushandura data dati.

Rudzi rwechipiri rwemetadata, inozivikanwa se analytics metadata inoita kuti mushandisi wekupedzisira aongorore zvirimo deta rekuchengeta kuwana i dati zviripo uye zvazvinoreva zvakajeka, zvisiri zvehunyanzvi.

Saka iyo analytics metadata inoshanda sebhiriji pakati pe deta rekuchengeta uye yekupedzisira-mushandisi application. Iyi metadata inogona kuve neiyo bhizinesi modhi, tsananguro dze dati inoenderana neiyo bhizinesi modhi, yakafanotsanangurwa mibvunzo uye mishumo, ruzivo rwekuwana mushandisi uye index.

Ongororo nekusimudzira metadata inofanirwa kusanganiswa kuita imwe yakabatanidzwa ine metadata kuti ishande nemazvo.

Nehurombo mazhinji ezvishandiso aripo ane yavo metadata uye parizvino hapana mazinga aripo ayo

bvumira maturusi ekuchengetedza data kuti abatanidze iyi metadata. Kugadzirisa mamiriro aya vatengesi vazhinji vevanotungamira maturusi ekuchengetedza data vakaumba Meta Data Council iyo yakazove Meta Data Coalition.

Chinangwa chemubatanidzwa uyu ndechekuvaka yakajairwa metadata seti inobvumira akasiyana data warehousing maturusi ekushandura metadata.
Kuedza kwavo kwakaguma nekuzvarwa kweMeta Data Interchange Specification (MDIS) iyo inobvumira kuchinjana kweruzivo pakati peMicrosoft archives uye ane hukama mafaera eMDIS.

Kuvapo kwe dati zvese zvakapfupikiswa / zvakaratidzwa uye zvakatsanangurwa, zvinopa mushandisi mukana wekuita DRILL DROWN (kuchera) kubva dati indexed kune dzakadzama uye zvinopesana. Kuvapo kwe dati nhoroondo yakadzama inobvumira kusikwa kwemaitiro ekuongorora nekufamba kwenguva. Mukuwedzera iyo metadata yekuongorora inogona kushandiswa se del dhairekitori Database Del deta rekuchengeta kubatsira vashandisi vekupedzisira kutsvaga i dati zvakakodzera.

Mukuenzanisa neOLTP masisitimu, nekugona kwavo kutsigira kuongororwa kwe dati uye kuzivisa, the deta rekuchengeta inoonekwa senzira yakakodzera yemaitiro eruzivo sekuita uye kupindura mibvunzo uye kugadzira mishumo. Chikamu chinotevera chicharatidza kusiyana kwemaitiro maviri aya zvakadzama.

DATA WAREHOUSE PANE OLTP SYSTEMS

Mazhinji ehurongwa hweruzivo mukati memasangano anoitirwa kutsigira mashandiro ezuva nezuva. Aya masisitimu anozivikanwa seOLTP SYSTEMS, anotora matranseks ezuva nezuva anogara achigadziridzwa.

I dati mukati meaya masisitimu anowanzo gadziridzwa, akawedzerwa kana kubviswa. Semuenzaniso, kero yemutengi inochinja sezvaanofamba kubva panzvimbo achienda kune imwe. Muchiitiko ichi kero itsva ichanyoreswa nekugadzirisa kero ndima ye Database. Chinangwa chikuru chezvirongwa izvi ndechekuderedza mari yekutengeserana uye panguva imwechete kuderedza nguva dzekugadzirisa. Mienzaniso yeOLTP Systems inosanganisira zviito zvakakomba senge kurongeka, kubhadhara, invoice, kugadzira, basa revatengi. vatengi.

Kusiyana neOLTP masisitimu, ayo akagadzirirwa kutengeserana uye chiitiko chakavakirwa maitiro, i deta rekuchengeta dzakagadzirwa kuti dzipe analytics-based process process rutsigiro dati uye maitiro ekuita sarudzo.

Izvi zvinowanzoitika nekubatanidza i dati kubva kwakasiyana siyana OLTP uye ekunze masisitimu mune imwechete "mudziyo" we dati, sezvakakurukurwa muchikamu chakapfuura.

Monash Data Warehousing Process Model

The process model for deta rekuchengeta Monash yakagadzirwa nevatsvakurudzi veMonash DSS Research Group uye inobva pane zvinyorwa zve deta rekuchengeta, ruzivo mukusimudzira masisitimu ekutsigira masisitimu, nhaurirano nevatengesi vekushandisa kuti vashandise deta rekuchengeta, paboka renyanzvi mukushandiswa kwe deta rekuchengeta.

Zvikamu izvi: Kutanga, Kuronga, Kubudirira, Kushanda uye Tsanangudzo. Dhiagiramu inotsanangura maitiro ekudzokorora kana kushanduka kwekugadzira a deta rekuchengeta nzira uchishandisa nzira mbiri-miseve yakaiswa pakati pezvikamu zvakasiyana. Muchirevo chechinyorwa chino "iterative" uye "evolutionary" zvinoreva kuti, padanho rega rega rekuita, zviitwa zvekuita zvinogona kugara zvichipararira kumashure kusvika padanho rakapfuura. Izvi zvinokonzerwa nemhando yeprojekti deta rekuchengeta umo zvikumbiro zvekuwedzera nemushandisi wekupedzisira zvinoitika chero nguva. Semuyenzaniso, panguva yekukura kwechiito deta rekuchengetaKana saizi itsva yezvidzidzo kana nzvimbo yakakumbirwa nemushandisi wekupedzisira, iyo yanga isiri chikamu chechirongwa chepakutanga, inofanira kuwedzerwa kuhurongwa. Izvi zvinokonzera kuchinja kweprojekti. Mhedzisiro yacho ndeyekuti timu yekugadzira inofanirwa kushandura zvinodiwa zvemagwaro akagadzirwa kusvika zvino panguva yechikamu chekugadzira. Muzviitiko zvakawanda, mamiriro azvino eprojekiti anofanirwa kudzokera kuchikamu chekugadzira uko chinodiwa chitsva chinofanira kuwedzerwa nekunyorwa. Mushandisi wekupedzisira anofanira kukwanisa kuona zvinyorwa zvakaongororwa uye shanduko dzakaitwa muchikamu chekusimudzira. Pakupera kwekutenderera uku, purojekiti inoda kuwana mhinduro yakanaka kubva kune zvese zvekusimudzira uye zvikwata zvevashandisi. Mhinduro inobva yashandiswa zvakare kunatsiridza chirongwa cheramangwana.

Capacity planning
dw inowanzova yakakura muhukuru uye inokura nekukurumidza (Best 1995, Rudin 1997a) nekuda kwehuwandu hwe dati nhoroondo yavanochengeta kubva panguva yavo. Kukura kunogonawo kukonzerwa ne dati ma-add-ons anokumbirwa nevashandisi kuti vawedzere kukosha kwe dati kuti vanotova nazvo. Nekuda kweizvozvo, zvinodiwa zvekuchengetedza zve dati inogona kuvandudzwa zvakanyanya (Eckerson 1997). Nokudaro, zvakakosha kuve nechokwadi, nekuita kuronga kwekugadzirisa, kuti hurongwa huchavakwa hunogona kukura sezvinodiwa zvinokura (Best 1995, LaPlante 1996, Lang 1997, Eckerson 1997, Rudin 1997a, Foley 1997a).
Pakuronga kuti data rehouse scalability, munhu anofanira kuziva kukura kunotarisirwa kukura muhukuru hwedura, mhando dzemibvunzo ingangoitwa, uye nhamba yevashandisi vekupedzisira vanotsigirwa (Best 1995, Rudin 1997b, Foley 1997a). Kuvaka scalable applications kunoda musanganiswa we scalable server technologies uye scalable application design techniques (Best 1995, Rudin 1997b. Zvose zviri zviviri zvakakosha pakuvaka scalable application. Scalable server technologies inogona kuita kuti zvive nyore uye zvinodhura kuwedzera kuchengetedza, ndangariro uye CPU pasina kuita kunonyadzisa (Lang 1997, Telephony 1997).

Pane maviri makuru scalable server matekinoroji: symmetric multiple processing (SMP) uye massively parallel processing (MPP) ) (IDC 1997, Humphries et al. 1999). Sevha yeSMP inowanzova nemapurosesa akawanda anogovera ndangariro, mabhazi ehurongwa, uye zvimwe zviwanikwa (IDC 1997, Humphries et al. 1999). Mamwe ma processor anogona kuwedzerwa kuwedzera ayo simba computational. Imwe nzira yekuwedzera simba computation yeSMP server, ndeyekubatanidza akawanda SMP michina. Iyi nzira inozivikanwa se clustering (Humphries et al. 1999). Sevha yeMPP, kune rumwe rutivi, ine mapurosesa akawanda imwe neimwe ine ndangariro yayo, hurongwa hwebhazi, uye zvimwe zviwanikwa (IDC 1997, Humphries et al. 1999). Imwe neimwe processor inonzi node. Kuwedzera kwe simba computational inogona kuwanikwa

kuwedzera mamwe nodes kumasevha eMPP (Humphries et al. 1999).

Hutera hwemasevha eSMP ndeyekuti akawandisa ekuisa-kubuda (I/O) mashandiro anogona kukanganisa hurongwa hwebhazi (IDC 1997). Dambudziko iri harisi kuitika mukati meMPP maseva sezvo processor yega yega ine yayo yebhazi system. Nekudaro, kubatanidza pakati peimwe node kunowanzo kunonoka kupfuura iyo SMP bhazi system. Uyezve, maseva eMPP anogona kuwedzera imwe nhanho yekuomarara kune vanogadzira application (IDC 1997). Saka, sarudzo pakati peSMP neMPP maseva inogona kupesvedzerwa nezvakawanda zvinhu, kusanganisira kuoma kwezvikumbiro, mutengo / kuita reshiyo, kubuda kunodiwa, dw maapplication anodzivirirwa uye kuwedzera kwehukuru hwe. Database yedw uye muhuwandu hwevashandisi vekupedzisira.

Nhamba dzinoverengeka dzemadhizaini ekushandisa dhizaini dzinogona kushandiswa mukuronga kugona. Mumwe anoshandisa nguva dzakasiyana dzekushuma semazuva, mavhiki, mwedzi nemakore. Kuve nenguva dzakasiyana dzekuzivisa, iyo Database inogona kupatsanurwa kuita zvidimbu zvakarongwa (Inmon et al. 1997). Imwe nzira ndeyekushandisa pfupiso matafura ayo anogadzirwa nekupfupikisa dati da dati zvakadzama. Saka, i dati zvipfupi zviri compact pane kutsanangurwa, izvo zvinoda shoma ndangariro nzvimbo. Saka iyo dati ruzivo runogona kuchengetwa kune isingadhure yekuchengetera unit, iyo inochengetedza yakatowanda kuchengetedza. Nepo kushandisa pfupiso matafura kunogona kuchengetedza nzvimbo yekuchengetera, inoda simba rakawanda kuti irambe iripo uye inoenderana nezvinodiwa zvebhizinesi. Nekudaro, nzira iyi inoshandiswa zvakanyanya uye inowanzo shandiswa pamwe chete neyakapfuura hunyanzvi (Best 1995, Inmon 1996a, Chauduri uye Dayal.
1997).

Kutsanangura Dhata Warehouse Technical Architectures Tsanangudzo yeDw Architecture matekiniki

Vatambi vekutanga vekuchengetera data vainyanya kufunga nezvepakati data warehouse kuitiswa uko zvese. dati, kusanganisira i dati zvekunze, zvakabatanidzwa mune imwechete,
muviri repository (Inmon 1996a, Bresnahan 1996, Peacock 1998).

Kubatsira kukuru kweiyi nzira ndeyekuti vashandisi vekupedzisira vanokwanisa kuwana iyo bhizinesi-yakafara maonero e dati sangano (Ovum 1998). Chimwe chekuwedzera ndechekuti inopa standardization ye dati pasangano rese, zvinoreva kuti pane vhezheni imwe chete kana tsananguro yeshoko rega rega rinoshandiswa mudw repository metadata (Flanagan naSafdie 1997, Ovum 1998). Kuipa kwenzira iyi, kune rumwe rutivi, ndeyokuti inodhura uye yakaoma kuvaka (Flanagan naSafdie 1997, Ovum 1998, Inmon et al. 1998). Pasina nguva mushure mekuchengetedza zvivakwa dati centralized yakave yakakurumbira, pfungwa yekuchera zvidiki-diki zvevamwari yakashanduka dati kutsigira zvinodiwa zvezvikumbiro zvakananga (Varney 1996, IDC 1997, Berson and Smith 1997, peacock 1998). Aya masisitimu madiki anotorwa kubva kune hombe deta rekuchengeta centralized. Vanopihwa mazita deta rekuchengeta mushandi wedhipatimendi kana mushandi data mats. Iyo inotsamira data mart architecture inozivikanwa sematatu-tiered architecture uko yekutanga tier ine deta rekuchengeta centralized, yechipiri ine dhipoziti ye dati yedhipatimendi uye yechitatu ine mukana wekuwana dati uye nematurusi ekuongorora (Demarest 1994, Inmon et al. 1997).

Data marts anowanzo kuvakwa mushure me deta rekuchengeta centralized yakavakwa kuti isangane nezvinodiwa zvezvikamu zvakananga (White 1995, Varney 1996).
Data marts store i dati zvinoenderana nemamwe mayuniti (Inmon et al. 1997, Inmon et al. 1998, IA 1998).

Kubatsira kweiyi nzira ndeyekuti panenge pasina dato isina kubatanidzwa uye kuti i dati ichave shoma shoma mukati me data marts kubva kune ese dati kubva kudhipoziti ye dati integrated. Imwe bhenefiti ndeyekuti pachave neashoma zvinongedzo pakati pega yega data mart uye masosi ayo dati nekuti yega yega data mart ine chete sosi ye dati. Uyezve neichi chivakwa chiri munzvimbo, vashandisi vekupedzisira vanogona vachiri kuwana iyo dati

masangano emakambani. Iyi nzira inozivikanwa seyepamusoro-pasi nzira, uko data marts inovakwa mushure meiyo deta rekuchengeta (peacock 1998, Goff 1998).
Kuwedzera kukosha kwekuratidza mhedzisiro nekukurumidza, mamwe masangano atanga kuvaka akazvimirira data marts (Flanagan naSafdie 1997, White 2000). Muchiitiko ichi, data marts inowana yavo dati zvakananga kubva kune zvakakosha zve dati OLTP uye isiri-OLTP kubva pakati uye yakabatanidzwa repository, nokudaro kubvisa kudiwa kwepakati repository panzvimbo.

Imwe neimwe data mart inoda kanenge imwe link kune yayo masosi dati. Imwe yakashata yekuve neakawanda zvinongedzo kune yega yega data mart ndeyekuti, zvichienzaniswa neakapfuura maviri ezvivakwa, kuwanda kwe dati inowedzera zvakanyanya.

Yese data mart inofanirwa kuchengetedza ese dati inodiwa munharaunda kusave nemhedzisiro paOLTP masisitimu. Izvi zvinokonzeresa i dati ivo vanochengetwa mune dzakasiyana data marts (Inmon et al. 1997). Chimwe chinokanganisa chekuvaka uku ndechekuti inotungamira mukugadzirwa kwekubatana kwakaoma pakati pe data marts uye yavo data masosi. dati izvo zvakaoma kushandisa uye kutonga (Inmon et al. 1997).

Chimwe chinokanganisa ndechekuti vashandisi vanogona kusakwanisa kuwana ruzivo rwekambani yekuongorora nekuti i dati yeakasiyana data mart haana kubatanidzwa (Ovum 1998).
Asi chimwe chinokanganisa ndechekuti panogona kunge paine inodarika tsananguro yeshoko rega rega rinoshandiswa mumateti e data rinoburitsa kusawirirana kwedata. dati musangano (Ovum 1998).
Pasinei nezvakashata zvakurukurwa pamusoro apa, standalone data marts ichiri kukwezva kufarira kwemasangano akawanda (IDC 1997). Chimwe chinhu chinoita kuti vataridzike ndechokuti vanokurumidza kukura uye vanoda nguva shoma uye zviwanikwa (Bresnahan 1996, Berson and Smith 1997, Ovum 1998). Nekuda kweizvozvo, ivo vanoshanda zvakanyanya semagadzirirwo ebvunzo anogona kushandiswa kukurumidza kuona mabhenefiti uye / kana zvikanganiso mudhizaini (Parsaye 1995, Braly 1995, Newing 1996). Muchiitiko ichi, chikamu chichaitwa muchirongwa chekuedza chinofanira kuva chiduku asi chakakosha kusangano (Newing 1996, Mansell-Lewis 1996).

Nekuongorora iyo prototype, vashandisi vekupedzisira uye manejimendi vanogona kusarudza kuenderera mberi kana kumisa chirongwa (Flanagan naSafdie 1997).
Kana sarudzo iri yekuenderera mberi, data marts yemamwe maindasitiri inofanira kuvakwa imwe panguva. Pane sarudzo mbiri dzevashandisi vekupedzisira zvichienderana nezvavanoda mukuvaka yakazvimirira data matrs: yakabatanidzwa/yakabatanidzwa uye isina kubatanidzwa (Ovum 1998)

Munzira yekutanga, yega yega data mart inofanirwa kuvakwa zvichienderana neazvino data mart uye modhi dati inoshandiswa nekambani (Varney 1996, Berson naSmith 1997, Peacock 1998). Kudikanwa kwekushandisa modhi dati yebhizinesi zvinoreva kuti munhu anofanirwa kuona kuti pane tsananguro imwe chete yeshoko rega rega rinoshandiswa pa data marts, zvakare kuona kuti akasiyana data marts anogona kubatanidzwa kuti ape tarisiro yeruzivo rwebhizinesi (Bresnahan 1996). Iyi nzira inonzi nzira yepasi-kumusoro uye inoshandiswa zvakanyanya kana paine chinotadzisa mari uye nguva (Flanagan and Safdie 1997, Ovum 1998, peacock 1998, Goff 1998). Mune yechipiri nzira, iyo yakavakwa data mart inogona kungogutsa zvinodiwa zveimwe unit. Musiyano weiyo federated data mart ndeye deta rekuchengeta akagoverwa umo iyo Database hub server middleware inoshandiswa kubatanidza akawanda data marts mune imwechete repository dati akaparadzirwa (White 1995). Muchiitiko ichi, i dati bhizinesi rakagoverwa mune akati wandei data mats. Zvikumbiro zvevashandisi vekupedzisira zvinotumirwa kune Database hub server middleware, iyo inobvisa zvese dati inokumbirwa nedata mats uye dyisa mhinduro kudzoka kune yekupedzisira-mushandisi maapplication. Iyi nzira inopa ruzivo rwebhizinesi kumagumo evashandisi. Nekudaro, matambudziko eakazvimiririra data mart haasati abviswa. Pane imwe architecture inogona kushandiswa inonzi iyo deta rekuchengeta chaiwo (White 1995). Nekudaro, iyi dhizaini, inoratidzwa muMufananidzo 2.9, haisi yekuchengetera data. dati chaiyo sezvo isingafambise mutoro kubva kuOLTP masisitimu kuenda deta rekuchengeta (Demarest 1994).

Chokwadi, zvikumbiro zve dati nevashandisi vekupedzisira ivo vanopfuudzwa kune OLTP masisitimu ayo anodzosera mhinduro mushure mekugadzirisa zvikumbiro zvemushandisi. Kunyange ichi chivakwa chichibvumira vashandisi vekupedzisira kuburitsa mishumo uye kuita zvikumbiro, haigone kupa i

dati nhoroondo uye pfupiso yeruzivo rwekambani kubvira i dati sezvo akasiyana OLTP masisitimu asina kubatanidzwa. Nokudaro, chivakwa ichi hachikwanisi kugutsa kuongororwa kwe dati zvakadai sekufembera.

Kusarudzwa kwekuwana uye data kudzoreredza maapplication dati

Chinangwa chekuvaka a deta rekuchengeta ndeyekusvitsa ruzivo kuvashandisi vekupedzisira (Inmon et al. 1997, Poe 1996, McFadden 1996, Shanks et al. 1997, Hammergren 1998); imwe kana kupfuura yekuwana uye kudzoreredza maapplication dati inofanira kupihwa. Kusvika pari zvino, kune zvakawanda zvakasiyana-siyana zvekushandiswa kwakadaro kune mushandisi kusarudza kubva (Hammergren 1998, Humphries et al. 1999). Izvo zvikumbiro zvakasarudzwa zvinotarisa kubudirira kwekuedza kwekuchengetedza dati musangano nekuti maapplication ndiwo anonyanya kuoneka chikamu che deta rekuchengeta kumushandisi wekupedzisira (Inmon et al. 1997, Poe 1996). Kubudirira a deta rekuchengeta, inofanirwa kukwanisa kutsigira mabasa ekuongorora data dati yemushandisi wekupedzisira (Poe 1996, Seddon naBenjamin 1998, Eckerson 1999). Nokudaro "nhanho" yezvinoda mushandisi wekupedzisira inofanira kuonekwa (Poe 1996, Mattison 1996, Inmon et al. 1997, Humphries et al. 1999).

Kazhinji, vashandisi vekupedzisira vanogona kuiswa muzvikamu zvitatu: vashandi vepamusoro, vaongorori vebhizimisi uye vashandisi vemasimba (Poe 1996, Humphries et al. 1999). Vashandisi vepamusoro vanoda kuwana nyore kune zvakafanotsanangurwa seti yemishumo (Humphries et al. 1999). Iyi mishumo inogona kuwanikwa zviri nyore nemenu navigation (Poe 1996). Pamusoro pazvo, mishumo inofanira kupa ruzivo ruchishandisa mufananidzo unomiririra sematafura nematemplate kuti ape ruzivo nekukurumidza (Humphries et al. 1999). Vaongorori vebhizinesi, avo vangave vasina ruzivo rwekugadzira mishumo kubva mukutanga vari voga, vanoda kukwanisa kushandura mishumo yemazuva ano kuti iite zvavanoda chaizvo (Poe 1996, Humphries et al. 1999). Vashandisi vesimba, kune rumwe rutivi, rudzi rwevashandisi vekupedzisira vane kugona kugadzira nekunyora zvikumbiro uye mishumo kubva pakutanga (Poe 1996, Humphries et al. 1999). Ndivo avo

vanovaka hukama kune mamwe marudzi evashandisi (Poe 1996, Humphries et al. 1999).

Kana zvinodikanwa zvemushandisi wekupedzisira zvatemwa, kusarudzwa kwekuwana uye kudzoreredza zvikumbiro zvinofanirwa kuitwa dati pakati pezvose zviripo (Poe 1996, Inmon et al. 1997).
Access to dati uye maturusi ekudzoreredza anogona kuiswa mumhando ina: OLAP chishandiso, EIS/DSS chishandiso, chebvunzo uye yekushuma, uye data yekuchera data.

OLAP zvishandiso zvinobvumira vashandisi kugadzira ad hoc mibvunzo pamwe neiyo yakagadzirwa pa Database Del deta rekuchengeta. Pamusoro pezvo, zvigadzirwa izvi zvinobvumira vashandisi kudonha kubva dati general kune zvakadzama.

Zvishandiso zveEIS/DSS zvinopa chirevo chepamusoro senge "ko kana" kuongorora uye kuwana mishumo inofambiswa nemenyu. Mishumo inofanirwa kufanotsanangurwa uye kusanganiswa nemamenu kuitira nyore kufamba.
Zvekubvunza uye zvekubika maturusi anobvumira vashandisi kugadzira yakafanotsanangurwa uye yakananga mishumo.

Maturusi ekuchera data anoshandiswa kuona hukama hunogona kuburitsa chiedza chitsva pamabasa akakanganikwa dati ye data warehouse.

Padivi pekugadzirisa zvinodikanwa zverudzi rwega rwemushandisi, maturusi akasarudzwa anofanirwa kuve anonzwisisika, anoshanda uye ari nyore kushandisa. Ivo zvakare vanofanirwa kuenderana nezvimwe zvikamu zvezvivakwa uye vanokwanisa kushanda nemasystem aripo. Inokurudzirwawo kusarudza kuwana data uye maturusi ekutora nemutengo unonzwisisika uye kuita. Mamwe maitiro ekutarisisa anosanganisira kuzvipira kwemutengesi kutsigira chigadzirwa chavo uye magadzirirwo aachave nawo mukuburitswa kunotevera. Kuti ive nechokwadi chekubatanidzwa kwemushandisi mukushandisa dura re data, timu yekuvandudza inosanganisira vashandisi mukuita sarudzo yezvishandiso. Muchiitiko ichi, kuongororwa kunoshanda kwemushandisi kunofanirwa kuitwa.

Kuti uwedzere kukosha kweiyo data warehouse timu yekuvandudza inogona zvakare kupa webhu kuwana kune yavo matura data. Iyo webhu-inogonesa data warehouse inobvumira vashandisi kuwana iyo dati kubva kunzvimbo dziri kure kana parwendo. Zvakare ruzivo runogona

kupihwa nemutengo wakaderera kuburikidza nekuderera kwemari yekudzidzira.

2.4.3 Dhata Warehouse Operation Phase

Ichi chikamu chine zviitwa zvitatu: tsananguro yezve data refresh marongero, kutonga kwe data warehouse zviitiko uye manejimendi ekuchengetedza data kuchengetedza.

Tsanangudzo yemaitiro ekuvandudza data

Mushure mekutakura kwekutanga, i dati nel Database yenzvimbo yekuchengetedza data inofanirwa kuzorodzwa nguva nenguva kuti ibudise shanduko dzakaitwa pa dati originals. Saka iwe unofanirwa kusarudza nguva yekuzorodza, kangani iyo yekuzorodza inofanira kurongwa uye nzira yekuzorodza iyo dati. Inokurudzirwa kuvandudza iyo dati apo iyo system inogona kutorwa kunze kwenyika. Chiyero chekuvandudza chinotarwa neboka rekusimudzira zvichienderana nezvinodiwa nemushandisi. Pane nzira mbiri dzekuzorodza iyo yekuchengetedza data: kuzorodza kuzere uye kuenderera kurodha kwekuchinja.

Nzira yekutanga, kuzorodza kuzere, inoda kurodha zvese dati kubva pakutanga. Izvi zvinoreva kuti zvose dati zvinodiwa zvinofanirwa kubviswa, kucheneswa, kushandurwa uye kubatanidzwa mune imwe neimwe yekuzorodza. Iyi nzira inofanirwa kudzivirirwa pese pazvinogoneka sezvo iri kutora nguva uye kushandisa zviwanikwa.

Imwe nzira ndeyekuramba uchiisa shanduko. Izvi zvinowedzera i dati izvo zvachinja kubva yekupedzisira data warehouse yekuzorodza kutenderera. Kuziva zvinyorwa zvitsva kana zvakashandurwa zvakanyanya kuderedza kuwanda kwe dati iyo inofanirwa kuparadzirwa kudura re data mune yega yega inogadziridza seizvi chete dati zvichawedzerwa Database ye data warehouse.

Pane angangoita mashanu maitiro anogona kushandiswa kubvisa i dati itsva kana kugadziridzwa. Kuti uwane inoshanda yekuvandudza vhidhiyo zano dati musanganiswa wemaitiro aya anotora shanduko dzese muhurongwa anogona kubatsira.

Nzira yekutanga, iyo inoshandisa timestamps, inofunga kuti munhu wese anopiwa dati yakagadziriswa uye yakagadziridzwa chitambi chenguva kuti iwe ugone kuziva zvese zviri nyore dati yakagadziridzwa uye itsva. Nekudaro, nzira iyi haisati yashandiswa zvakanyanya mumasevhisi mazhinji nhasi.
Yechipiri maitiro ndeye kushandisa application-yakagadzirwa delta faira iyo ine chete shanduko dzakaitwa kune iyo dati. Kushandisa iyi faira kunowedzerawo kutenderera kwekuvandudza. Zvisinei, kunyange iyi nzira haisati yashandiswa mumashandisirwo akawanda.
Nzira yechitatu ndeyekutarisa faira regi, iro rine ruzivo rwakafanana neiyo delta faira. Musiyano chete ndewekuti faira regi rakagadzirirwa kudzoreredza maitiro uye rinogona kunetsa kunzwisisa.
Nzira yechina ndeyekugadzirisa kodhi yekushandisa. Nekudaro, yakawanda kodhi yekushandisa ndeyekare uye brittle; saka nzira iyi inofanira kudziviswa.
Nzira yekupedzisira ndeyekuenzanisa i dati masosi ane main file dei dati.

Kutariswa kwezviitiko zvekuchengetedza data

Kana iyo yekuchengetedza data yaburitswa kune vashandisi, inofanirwa kuongororwa nekufamba kwenguva. Mune ino kesi, iyo data warehouse maneja anogona kushandisa imwe kana akawanda manejimendi uye ekudzora maturusi ekutarisa mashandisirwo e data warehouse. Kunyanya, ruzivo runogona kuunganidzwa pane vanhu uye nenguva yavanowana mudura re data. Handeyi nazvo dati yakaunganidzwa, nhoroondo yebasa rakaitwa inogona kugadzirwa iyo inogona kushandiswa seyekupinza mukushandiswa kwemushandisi yekudzosera kumashure. Chargeback inobvumira vashandisi kuziviswa nezve data warehouse yekugadzirisa mutengo.

Pamusoro pezvo, data rehouse auditing inogonawo kushandiswa kuona mhando dzemibvunzo, saizi yavo, nhamba yemibvunzo pazuva, nguva dzemhinduro dzemubvunzo, zvikamu zvakasvikwa, uye huwandu hwemibvunzo. dati processed. Chimwe chinangwa chekuita data warehouse auditing ndechekuziva dati izvo zvisiri kushandiswa. Izvi dati vanogona kubviswa kubva mudura re data kuti vavandudze nguva

yemibvunzo kuuraya mhinduro uye kutonga kukura kwe dati vanogara mukati me data base ye data warehouse.

Data warehouse security management

Imwe data warehouse ine dati zvakabatanidzwa, zvakakosha, zvinonzwisisika zvinogona kusvika nyore nyore. Nokuda kwechikonzero ichi inofanira kuchengetedzwa kubva kune vashandisi vasina kubvumirwa. Imwe nzira yekushandisa kuchengetedza ndeye kushandisa iyo del basa DBMS kupa ropafadzo dzakasiyana kumhando dzakasiyana dzevashandisi. Nenzira iyi, mbiri yekuwana inofanirwa kuchengetedzwa kune yega yega mushandisi. Imwe nzira yekuchengetedza iyo yekuchengetedza data ndeyekuinyorera sezvakanyorwa mu data base ye data warehouse. Access to dati uye maturusi ekudzoreredza anofanirwa kudzima iyo dati usati wapa mhinduro kune vashandisi.

2.4.4 Dhata Warehouse Deployment Phase

Ndiyo nhanho yekupedzisira mune data warehouse kuita kutenderera. Zviitwa zvinofanirwa kuitwa muchikamu ichi zvinosanganisira kudzidzisa vashandisi kushandisa dura re data uye kuita ongororo yedura re data.

Kudzidziswa kwemushandisi

Kudzidziswa kwemushandisi kunofanirwa kuitwa usati wasvika dati yenzvimbo yekuchengetedza data uye kushandiswa kwezvishandiso zvekutora. Kazhinji, zvirongwa zvinofanirwa kutanga nesumo yepfungwa yekuchengetedza dati, zviri mukati medura re data, meta dati uye zvakakosha zvezvishandiso. Zvadaro, vashandisi vepamberi vanogonawo kudzidza matafura emuviri uye maficha evashandisi vekuwana data uye maturusi ekutora.

Pane nzira dzakawanda dzekuita mushandisi kudzidzisa. Imwe yeiyi inosanganisira kusarudzwa kwevashandisi vazhinji kana vaongorori vakasarudzwa kubva mudziva revashandisi, zvichibva pautungamiri hwavo uye hunyanzvi hwekutaurirana. Ava vanodzidziswa pachedu pane zvese zvavanoda kuziva kuti vajairane nehurongwa. Mushure mekudzidziswa, vanodzokera kumabasa avo uye vanotanga kudzidzisa vamwe vashandisi mashandisiro ehurongwa. Pa

Zvichienderana nezvavakadzidza, vamwe vashandisi vanogona kutanga kuongorora dura re data.
Imwe nzira ndeyekudzidzisa vashandisi vazhinji panguva imwe chete, sekunge uri kudzidzira mukirasi. Iyi nzira yakakodzera kana paine vashandisi vakawanda vanoda kudzidziswa panguva imwe chete. Asi imwe nzira ndeyekudzidzisa mushandisi wega wega, mumwe nemumwe. Iyi nzira yakakodzera kana paine vashoma vashandisi.

Chinangwa chekudzidziswa kwemushandisi ndechekuziva iwe nekuwana dati uye maturusi ekudzoreredza pamwe chete nezvirimo mudura re data. Nekudaro, vamwe vashandisi vanogona kuremerwa nehuwandu hweruzivo rwakapihwa panguva yekudzidziswa. Zvino chiverengero chezvidzidzo zvekuvandudza chinoda kuitwa kuti chirambe chichitsigirwa uye kupindura mibvunzo chaiyo. Mune zvimwe zviitiko, boka revashandisi rinoumbwa kuti ripe rudzi urwu rwerutsigiro.

Kuunganidza mhinduro

Kana iyo yekuchengetedza data yaburitswa, vashandisi vanogona kushandisa i dati kugara mudura re data nekuda kwezvinangwa zvakasiyana. Kazhinji, vaongorori kana vashandisi vanoshandisa i dati mudura re data re:

1. 1 Ziva mafambiro ekambani
2. 2 Ongorora maitiro ekutenga e vatengi
3. 3 Kupatsanura i vatengi uye ye
4. 4 Ipa masevhisi akanakisa kune vatengi - gadzirisa masevhisi
5. 5 Gadzira mazano Marketing
6. 6 Ita makotesheni emakwikwi ekuongorora mutengo uye kubatsira kudzora
7. 7 Tsigira hurongwa hwekuita sarudzo
8. 8 Ziva mikana yokubuda nayo
9. 9 Kuvandudza kunaka kwemaitiro ebhizinesi aripo
10. 10 Tarisa purofiti

Kutevera gwara rekusimudzira kwenzvimbo yekuchengetera data, nhevedzano yeongororo yehurongwa inogona kuitwa kuti uwane mhinduro

zvese nechikwata chebudiriro uye nevekupedzisira-mushandisi nharaunda.
Mhedzisiro yakawanikwa inogona kuverengerwa kune inotevera kutenderera kutenderera.

Sezvo nzvimbo yekuchengetera data ine nzira yekuwedzera, zvakakosha kuti udzidze kubva mukubudirira uye kukanganisa kwezvakamboitika.

2.5 Pfupiso

Muchitsauko chino nzira dziripo muzvinyorwa dzakurukurwa. Muchikamu 1 pfungwa yekuchengetera data uye basa rayo musarudzo sainzi yakakurukurwa. Chikamu 2 chakatsanangura misiyano mikuru pakati pematura data neOLTP masisitimu. Chikamu 3 chakakurukura nezveMonash data warehouse model iyo yakashandiswa muchikamu chechina kutsanangura zviitiko zvinosanganisirwa mukugadzira dura re data, izvi zvikumbiro hazvina kubva pakutsvaga kwakasimba. Chii chinoitika muchokwadi chinogona kunge chakasiyana kwazvo kubva kune izvo zvinyorwa zvinoshumwa, zvisinei mhedzisiro iyi inogona kushandiswa kugadzira bhegi rekutanga rinotsikirira pfungwa yekuchengetera data yetsvagurudzo iyi.

Chitsauko 3

Tsvagiridzo uye nzira dzekugadzira

Chitsauko ichi chinobata netsvakiridzo nemagadzirirwo echidzidzo ichi. Chikamu chekutanga chinoratidza maonero akajairika enzira dzekutsvagisa dziripo dzekutsvagisa ruzivo, uyezve maitiro ekusarudza nzira yakanakisa yeimwe chidzidzo anokurukurwa. Muchikamu chechipiri nzira mbiri dzakasarudzwa nemaitiro ari pamusoro dzinobva dzakurukurwa; chimwe cheizvi chichasarudzwa chogashirwa nokuda kwezvikonzero zvakarongwa muchikamu chechitatu apo zvikonzero zvekusabatanidzwa kwechimwe chimiso zvakatarwawo. Chikamu 2 chinopa purojekiti yekutsvaga uye chikamu 3 mhedziso.

3.1 Tsvagiridzo mumasisitimu eruzivo

Tsvagiridzo yehurongwa hweruzivo haingogumiri kunharaunda yetekinoroji asi inofanirawo kuwedzerwa kuti ibatanidze zvinangwa zvemaitiro nesangano.
Tine chikwereti ichi kune zvinyorwa zvezvidzidzo zvakasiyana-siyana kubva kumagariro evanhu kusvika kune echisikigo; izvi zvinotungamira pakudiwa kweimwe nzira dzetsvakiridzo dzinosanganisira nzira dzehuwandu uye dzemhando dzinofanirwa kushandiswa kune masisitimu eruzivo.
Nzira dzose dziripo dzekutsvakurudza dzakakosha, chaizvoizvo vatsvakurudzi vakati wandei vakaita saJenkins (1985), Nunamaker et al. (1991), uye Galliers (1992) vanoti hapana nzira chaiyo yepasi rose yekuita tsvakurudzo mune zvakasiyana-siyana zvehurongwa hwemashoko; kutaura zvazviri imwe nzira inogona kukodzera imwe tsvagiridzo asi kwete kune vamwe. Izvi zvinotitungamira kukuda kwekusarudza nzira inokodzera yedu chaiyo purojekiti yekutsvagisa: yesarudzo iyi Benbasat et al. (1987) vanoti chimiro nechinangwa chetsvakiridzo zvinofanirwa kutariswa.

3.1.1 Mamiriro etsvakurudzo

Nzira dzakasiyana-siyana-dzakavakirwa patsvagiridzo dzinogona kuiswa mutsika nhatu dzinozivikanwa zvakanyanya musainzi yeruzivo: positivist, kududzira, uye tsvagiridzo yakakosha.

3.1.1.1 Positivist research

Positivist research inozivikanwawo sesainzi kana empirical kudzidza. Inotsvaka: "kutsanangura uye kufanotaura zvichaitika munyika yemagariro evanhu nekutarisa nguva dzose uye chikonzero-chinokonzera hukama pakati pezvinhu zvinoumba" (Shanks et al 1993).

Tsvagiridzo yePositivist inoratidzirwawo nekudzokorora, kurerutsa uye kuramba. Uyezve, tsvakiridzo yepositivist inobvuma kuvepo kwehukama hwepamberi pakati pezviitiko zvakadzidzwa.
Sekureva kwaGalliers (1992) taxonomy inzira yekutsvagisa inosanganisirwa mune positivist paradigm, iyo zvisinei haina kuganhurirwa kune izvi, chokwadi kune ma laboratory kuyedza, bvunzo dzemumunda, nyaya dzenyaya, theorem demonstrations, kufanotaura uye kuenzanisa. Vachishandisa nzira idzi, vaongorori vanobvuma kuti zviitiko zvakadzidzwa zvinogona kucherechedzwa zvine mutsindo uye zvakasimba.

3.1.1.2 Tsvakurudzo yekududzira

Tsvakurudzo yekududzira, iyo inowanzonzi phenomenology kana anti-positivism inotsanangurwa naNeuman (1994) se "kuongororwa kwakarongeka kwezvinoreva zvemagariro echiito kuburikidza nekutarisa kwakananga uye kwakadzama kwevanhu vari mumamiriro ezvinhu echisikigo, kuti vasvike pakunzwisisa uye nekunzwisisa. dudziro yekuti vanhu vanogadzira sei nekuchengetedza nyika yavo yemagariro”. Zvidzidzo zvekududzira zvinoramba fungidziro yekuti zvakacherechedzwa zviitiko zvinogona kucherechedzwa zvine chinangwa. Muchokwadi iwo akavakirwa pane subjective dudziro. Pamusoro pezvo, vaongorori vanodudzira havaisi chirevo chekutanga pane izvo zvavanodzidza.

Iyi nzira inosanganisira zvidzidzo zvepfungwa / zvenharo, tsvakiridzo yechiito, zvidzidzo zvinotsanangura/zvinodudzira, tsvakiridzo yeramangwana, uye kuita-kutamba. Pamusoro peongororo idzi uye nyaya dzenyaya dzinogona kuverengerwa mune iyi nzira sezvo dzine chekuita nezvidzidzo zvevanhu kana masangano mukati memamiriro ezvinhu akaomarara enyika.

3.1.1.3 Tsvakurudzo yakakosha

Kutsvaga kwakakosha ndiyo nzira isinganyanyozivikanwa musainzi yemagariro asi ichangobva kugamuchira tarisiro yevaongorori munhandare yeruzivo. Mafungiro ehuzivi kuti chokwadi chevanhu chakaitwa kare uye chinobudiswa nevanhu, pamwe chete nehurongwa hwemagariro evanhu nezviito zvavo nekubatana. Kugona kwavo, zvisinei, kunoyananiswa nehuwandu hwemagariro, tsika nezvematongerwo enyika.

Kufanana netsvakiridzo yekududzira, tsvakiridzo yakakosha inopokana kuti tsvakiridzo yepositivist haina chekuita nemagariro uye inofuratira simba rayo pane zviito zvevanhu.
Tsvagiridzo yakakosha, kune rumwe rutivi, inoshoropodza tsvakiridzo yekududzira nekuda kwekunyanya kuzviisa pasi uye nekusagadzirira kubatsira vanhu kuvandudza hupenyu hwavo. Musiyano mukuru pakati pekutsvagisa kwakakosha uye dzimwe nzira mbiri ndiyo yekuongorora kwayo. Nepo chinangwa chepositivist uye tsika dzekududzira chiri kufanotaura kana kutsanangura mamiriro ezvinhu kana kuti magariro echokwadi, tsvakiridzo yakakosha ine chinangwa chekuongorora zvakadzama nekushandura chokwadi chemagariro pasi pechidzidzo.

Vatsvakurudzi vakaoma vanowanzopikisa mamiriro ezvinhu kuitira kuti vabvise misiyano yemagariro evanhu uye kugadzirisa mamiriro evanhu. Tsvagiridzo yakakosha ine kuzvipira kune maitiro ekuona kwezviitiko zvekufarira uye, saka, kazhinji irefu. Mienzaniso yenzira dzekutsvagisa ndeyenguva refu yenhoroondo zvidzidzo uye ethnographic zvidzidzo. Kutsvaga kwakakosha, zvisinei, hakuna kushandiswa zvakanyanya mukutsvaga kwehurongwa hweruzivo

3.1.2 Chinangwa chetsvakiridzo

Pamwe chete nechimiro chetsvakiridzo, chinangwa chayo chinogona kushandiswa kutungamira muongorori pakusarudza imwe nzira yekutsvaga. Hukuru hwepurojekiti yekutsvagisa hune hukama zvakanyanya nenzvimbo yetsvagiridzo ine chekuita nekutenderera kwetsvakiridzo iyo ine zvikamu zvitatu: kuvaka dzidziso, kuongorora dzidziso uye kunatsiridza dzidziso. Nokudaro, zvichibva pakukurumidza maererano nekutenderera kwekutsvakurudza, chirongwa chekutsvakurudza chinogona kuva nechinangwa chinotsanangura, chinotsanangura, chekuongorora, kana chekufungidzira.

3.1.2.1 Tsvakurudzo yekuongorora

Tsvagiridzo yekuongorora ine chinangwa chekuongorora chinyorwa chitsva uye kugadzira mibvunzo uye fungidziro dzekutsvaga mune ramangwana. Rudzi urwu rwekutsvagisa runoshandiswa mukuvaka dzidziso kuwana mareferenzi ekutanga munzvimbo itsva. Kazhinji nzira dzekutsvagisa dzemhando yepamusoro dzinoshandiswa, senge nyaya dzezvidzidzo kana zvidzidzo zvephenomenological.

Nekudaro, zvinogoneka zvakare kushandisa nzira dzehuwandu senge ongororo yekuongorora kana kuyedza.

3.1.3.3 Tsvakiridzo ine tsananguro

Tsvagiridzo inotsanangura yakagadzirirwa kuongorora nekutsanangura zvakadzama mamiriro ezvinhu kana maitiro esangano. Izvi zvakakodzera pakuvaka dzidziso uye zvinogona zvakare kushandiswa kusimbisa kana kupikisa fungidziro. Tsvakurudzo inotsanangura kazhinji inosanganisira kushandiswa kwezviyero uye sampuli. Nzira dzekutsvaga dzakakodzera dzinosanganisira ongororo uye ongororo yemashure.

3.1.2.3 Tsvakurudzo yetsanangudzo

Tsvakurudzo inotsanangura inoedza kutsanangura kuti sei zvinhu zvichiitika. Inovaka pachokwadi chakatodzidzwa uye inoedza kutsvaga chikonzero chechokwadi ichocho.
Nokudaro tsvakurudzo yetsanangudzo inowanzovakirwa pamusoro pekutsvaga kana tsvakurudzo yetsanangudzo uye inoenderana nekuedza nekunatsa dzidziso. Tsvagiridzo inotsanangura inowanzo shandisa zvidzidzo zvenyaya kana ongororo-yakavakirwa nzira dzekutsvagisa.

3.1.2.4 Tsvakurudzo yekufungidzira

Preemptive research inovavarira kufanotaura zviitiko zvakaonekwa uye maitiro ari kudzidzwa (Marshall naRossman 1995). Kufembera ndiwo muyedzo wesainzi wechokwadi. Rudzi urwu rwekutsvagisa runowanzo shandisa ongororo kana kuongorora data dati vanyori venhoroondo. (Yin 1989)

Hurukuro iri pamusoro inoratidza kuti kune dzinoverengeka nzira dzetsvakiridzo dzinogona kushandiswa mune chimwe chidzidzo. Nekudaro, panofanirwa kuve neimwe nzira yakanyatsokodzera kupfuura dzimwe kune imwe mhando yepurojekiti yekutsvaga. (Galliers 1987, Yin 1989, De Vaus 1991). Naizvozvo, muongorori wega wega anofanirwa kunyatsoongorora kusimba uye kusasimba kwemaitiro akasiyana, kuti atore nzira yetsvakiridzo yakanyatsokodzera inoenderana nepurojekiti yekutsvaga. (Jenkins 1985, Pervan naKlass 1992, Bonomia 1985, Yin 1989, Himilton naIves 1992).

3.2. Nzira dzekutsvaga dzinogona kuitika

Chinangwa chechirongwa ichi chaive chekudzidza ruzivo rwemasangano emuAustralia ane i dati yakachengetwa nekuvandudzwa kwe deta rekuchengeta. zuva kuti, pari zvino, pane kushomeka kwekutsvagisa munzvimbo yekuchengetera data muAustralia, chirongwa ichi chekutsvagisa chichiri muchikamu chedzidziso chekutenderera kwekutsvagisa uye chine chinangwa chekuongorora. Kuongorora chiitiko mumasangano eAustralia anotora data warehousing kunoda kududzira nzanga chaiyo. Nekuda kweizvozvo, fungidziro yehuzivi iri pasi pechirongwa chekutsvagisa inotevera dudziro yechinyakare.

Mushure mekunyatsoongorora nzira dziripo, nzira mbiri dzinogona kutsvakurudza dzakaonekwa: tsvakurudzo uye zvidzidzo zvechiitiko, zvinogona kushandiswa pakutsvakurudza kwekuongorora (Shanks et al. 1993). Galliers (1992) anoti kukodzera kwenzira mbiri idzi dzechidzidzo ichi muongororo yake yakadzokororwa yetaxonomy achiti dzakakodzera kuvakwa kwedzidziso. Zvikamu zviviri zvinotevera zvinokurukura nzira imwe neimwe zvakadzama.

3.2.1 Nzira yekuongorora tsvakurudzo

Nzira yekutsvagisa ongororo inobva kunzira yekare yekuverenga vanhu. Census ndeyekuunganidza ruzivo kubva kuvanhu vese. Iyi nzira inodhura uye haishandi, kunyanya kana vanhu vakawanda. Saka, kana ichienzaniswa nekuverenga vanhu, ongororo inowanzotarisana nekuunganidza ruzivo rwenhamba diki, kana sampuli, yevamiriri vehuwandu (Fowler 1988, Neuman 1994). Muenzaniso unoratidza huwandu hwevanhu kwainotorwa, ine madhigirii akasiyana ekururama, zvichienderana nemuenzaniso wechimiro, saizi, uye nzira yekusarudza yakashandiswa (Fowler 1988, Babbie 1982, Neuman 1994).

Nzira yekuongorora inotsanangurwa se "zvishoma zvemaitiro, mamiriro kana maonero pane imwe nguva nenguva, akaitwa uchishandisa mibvunzo kana kubvunzurudza, kubva panogona kubva kufungidzira.
made” (Galliers 1992:153) [kutorwa kwemifananidzo yezviitwa, mamiriro ezvinhu kana maonero pane imwe nhambo nenguva, yakatorwa pachishandiswa mibvunzo kana bvunzurudzo, panogona kufungidzira]. Ongororo ine chekuita nekuunganidza ruzivo nezvezvimwe zvikamu zvechidzidzo kubva kune vakati wandei vevatori vechikamu kuburikidza nekubvunza mibvunzo (Fowler 1988). Aya mibvunzo uye kubvunzurudza, izvo zvinosanganisira kutarisana parunhare kubvunzurudza uye kubvunzurudzwa kwakarongeka, zvakare maitiro ekuunganidza. dati inoshandiswa muongororo (Blalock 1970, Nachmias neNachmias 1976, Fowler 1988), ongororo nekuongorora zvinogona kushandiswa (Gable 1994). Panzira dzese idzi dzekuunganidza vamwari dati, kushandiswa kwemibvunzo ndiyo inonyanya kufarirwa nzira, sezvo inovimbisa kuti i dati

inounganidzwa yakarongeka uye yakarongwa, uye nokudaro inofambisa kugoverwa kwemashoko (Hwang 1987, de Vaus 1991).

Mukuongorora i dati, nzira yekuongorora inowanzoshandisa nzira dzehuwandu, dzakadai sekuongorora nhamba, asi maitiro ehutano anogonawo kushandiswa (Galliers 1992, Pervan

naKlass 1992, Gable 1994). Kazhinji, i dati yakaunganidzwa inoshandiswa kuongorora kugoverwa uye maitiro emasangano (Fowler 1988).

Kunyangwe ongororo dzakakodzerwa nekutsvaga kunobata nemubvunzo wekuti 'chii?' (chii) kana kubva mairi, senge 'quanto' (yakawanda sei) uye 'quant'è' (ingani), vanogona kubvunzwa kuburikidza nemubvunzo 'sei' (Sonquist naDunkelberg 1977, Yin 1989). Sekureva kwaSonquist naDunkelberg (1977), tsvakiridzo yekutsvagisa ine chinangwa chekufungidzira kwakaoma, zvirongwa zvekuongorora, kutsanangura huwandu hwevanhu uye kugadzira mhando dzehunhu hwevanhu. Uyezve, ongororo dzinogona kushandiswa kudzidza maonero evamwe vanhu, mamiriro ezvinhu, zvinotendwa, hunhu, zvinotarisirwa uye hunhu hwekare kana hwazvino (Neuman 1994).

Ongororo inobvumira muongorori kuti awane hukama hwevanhu uye mhedzisiro yacho kazhinji yakawanda kupfuura dzimwe nzira (Sonquist naDunkelberg 1977, Gable 1994). Ongororo inobvumira vaongorori kuti vatarise nzvimbo yakakura uye kuti vasvike nhamba huru dzevakapindura (Blalock 1970, Sonquist naDunkelberg 1977, Hwang naLin 1987, Gable 1994, Neuman 1994). Chekupedzisira, ongororo dzinogona kupa ruzivo rusingawanikwe kune imwe nzvimbo kana mune fomu inodiwa pakuongorora (Fowler 1988).

Pane, zvisinei, zvimwe zvinotadzisa kuita ongororo. Chisina kunaka ndechekuti muongorori haakwanise kuwana ruzivo rwakawanda nezvechinhu chakadzidzwa. Izvi zvinokonzerwa nekuti ongororo dzinoitwa chete pane imwe nguva uye, nekudaro, kune mashoma mashoma emhando dzakasiyana uye vanhu izvo muongorori anogona.

kudzidza (Yin 1989, de Vaus 1991, Gable 1994, Denscombe 1998). Chimwe chinokanganisa ndechekuti kuita ongororo kunogona kudhura zvakanyanya maererano nenguva uye zviwanikwa, kunyanya kana zvichisanganisira kubvunzana vakatarisana (Fowler 1988).

3.2.2. Inquiry Research Method

Nzira yekutsvakurudza yekubvunzurudza inosanganisira kuongorora kwakadzama kweimwe mamiriro mukati memamiriro ayo chaiwo pane imwe nguva yakatsanangurwa, pasina kupindira kune chikamu chemuongorori (Shanks & C. 1993, Eisenhardt 1989, Jenkins 1985). Kunyanya nzira iyi inoshandiswa kutsanangura hukama huri pakati pezvinyorwa zviri kudzidzwa mune imwe mamiriro ezvinhu (Galliers 1992). Tsvakurudzo inogona kusanganisira nyaya imwechete kana dzakawanda, zvichienderana nechiitiko chakaongororwa (Franz naRobey 1987, Eisenhardt 1989, Yin 1989).

Nzira yekutsvagisa yekubvunzurudza inotsanangurwa se "kubvunza kwakasimba kunoongorora chiitiko chemazuva ano mukati memamiriro acho chaiwo, uchishandisa akawanda masosi akatorwa kubva kune chimwe kana akawanda masangano akadai sevanhu, mapoka, kana masangano" (Yin 1989). Hapana kupatsanurwa kwakajeka pakati pechiitiko uye mamiriro ayo uye hapana kutonga kana kuedza kushandiswa kwezvinhu zvakasiyana-siyana (Yin 1989, Benbasat et al. 1987).

Pane nzira dzakasiyana dzekuunganidza vamwari dati iyo inogona kushandiswa nenzira yekubvunzurudza, iyo inosanganisira kutarisisa kwakananga, kudzokorora rekodhi rekodhi, mibvunzo yemibvunzo, kuongorora zvinyorwa, uye kubvunzurudza kwakarongwa. Kuve nemhando dzakasiyana-siyana dzekukohwa dati, tsvakurudzo dzinobvumira vatsvakurudzi kubata nezvose dati hunhu uye huwandu panguva imwe chete (Bonoma 1985, Eisenhardt 1989, Yin 1989, Gable 1994). Sezvinoita nenzira yeongororo, muongorori weongororo anoshanda semucherechedzi kana muongorori uye kwete semutori wechikamu anoshanda musangano riri kudzidza.

Benbasat et al. (1987) vanoti nzira yekubvunzurudza inonyanya kukodzera kutsvagisa dzidziso yekuvaka, iyo inotanga nemubvunzo wekutsvaga uye inoenderera nekudzidziswa.

yedzidziso panguva yekuunganidza dati. Kuvawo akakodzera pachikuva

of theory building, Franz naRobey (1987) vanoratidza kuti nzira yekubvunzurudza inogona kushandiswawo pachikamu chedzidziso yakaoma. Muchiitiko ichi, zvichibva pauchapupu hwakaunganidzwa, dzidziso yakapihwa kana fungidziro inosimbiswa kana kurambidzwa. Pamusoro pezvo, kubvunza kwakakodzerawo kutsvagurudzo ine chekuita nemibvunzo yekuti 'sei' kana 'sei' (Yin 1989).

Zvichienzaniswa nedzimwe nzira, ongororo dzinobvumira muongorori kutora ruzivo rwakakosha mune zvakadzama (Galliers 1992, Shanks et al. 1993). Uyezve, ongororo dzinobvumira muongorori kuti anzwisise hunhu uye kuoma kwemaitiro akadzidzwa (Benbasat et al. 1987).

Pane zvipingamupinyi zvina zvikuru zvine chekuita nenzira yekubvunza. Chekutanga kushaikwa kwekudzora kubviswa. Kuzviisa pasi kwemuongorori kunogona kushandura mhedzisiro uye mhedziso dzechidzidzo (Yin 1989). Chechipiri chinokanganisa kushaikwa kwekutarisa kunodzorwa. Kusiyana nenzira dzekuyedza, muongorori wekubvunza haakwanise kudzora zviitiko zvakadzidzwa sezvo zvichiongororwa mumamiriro avo echisikigo (Gable 1994). Kukanganisa kwechitatu ndiko kushaikwa kwekudzokorora. Izvi zvinokonzerwa nekuti muongorori haakwanise kuona zviitiko zvakafanana, uye haakwanise kuburitsa mhedzisiro yeimwe ongororo (Lee 1989). Pakupedzisira, semugumisiro wekusadzokororwa, zvakaoma kutsanangura zvabuda kubva kune imwe kana kupfuura ongororo (Galliers 1992, Shanks et al. 1993). Matambudziko ose aya, zvisinei, haakundiki uye anogona, kutaura zvazviri, kudzikiswa nemuongorori nekushandisa zviito zvakakodzera (Lee 1989).

3.3. Ruramisa nzira yekutsvagisa kugamuchirwa

Kubva panzira mbiri dzinobvira dzetsvakiridzo dzechidzidzo ichi, nzira yeongororo inoonekwa seyakanyanya kukodzera. Wekuferefeta akarambwa zvichitevera kunyatsotariswa kwakabatana

zvakanaka uye utera. Kunaka kana kusakodzera nzira yega yega yechidzidzo ichi inokurukurwa pazasi.

3.3.1. Nzira yekutsvakurudza isina kufanira yekubvunza

Nzira yekubvunzurudza inoda kuongororwa kwakadzama kweimwe mamiriro mukati meimwe kana mamwe masangano pane imwe nguva yenguva (Eisenhardt 1989). Pakadai, nguva inogona kudarika nguva yakapihwa yechidzidzo ichi. Chimwe chikonzero chekusatora nzira yekubvunza ndechekuti mhedzisiro inogona kutambura nekushaikwa kwekuomarara (Yin 1989). Kuzviisa pasi kwemuongorori kunogona kukanganisa mhedzisiro uye mhedziso. Chimwe chikonzero ndechekuti nzira iyi yakanyatsokodzera kutsvagisa mibvunzo yerudzi rwe'how' kana 'why' (Yin 1989), nepo mubvunzo wetsvakiridzo wechidzidzo ichi uri we'chii'. Chekupedzisira asi chisiri chidiki, zvinonetsa kuburitsa zvakawanikwa kubva muongororo imwe chete kana shoma (Galliers 1992, Shanks et al. 1993). Zvichienderana nechikonzero ichi, nzira yekutsvagisa ongororo haina kusarudzwa sezvo yanga isingakodzeri chidzidzo ichi.

3.3.2. Kunaka kwenzira yekutsvaga ye kuferefeta

Pakaitwa tsvagiridzo iyi, tsika yekuchengetera data yakanga isati yave yakagamuchirwa zvakanyanya nemasangano eAustralia. Nekudaro, pakanga pasina ruzivo rwakawanda maererano nekuita kwavo mukati memasangano eAustralia. Ruzivo rwuripo rwakabva kumasangano akange aita kana kushandisa a deta rekuchengeta. Panyaya iyi, nzira yekutsvagisa ongororo ndiyo inonyanya kukodzera sezvo ichibvumira kuwana ruzivo rwusingawanikwe kumwe kunhu kana muchimiro chinodiwa pakuongorora (Fowler 1988). Pamusoro pezvo, nzira yekutsvagisa yekubvunzurudza inobvumira muongorori kuwana nzwisiso yakanaka yemaitiro, mamiriro, kana maonero panguva yakatarwa (Galliers 1992, Denscombe 1998). Pfupiso yakakumbirwa kusimudzira ruzivo rweAustralia data warehousing ruzivo.

Pamusoro pazvo, Sonquist naDunkelberg (1977) vanoti tsvakiridzo yetsvakiridzo mhedzisiro yakawanda kupfuura dzimwe nzira.

3.4. Survey Research Design

Iyo data warehousing practice ongororo yakaitwa muna 1999. Vaitarisirwa vanhu vaive nemasangano eAustralia aifarira zvidzidzo zvekuchengetedza data, sezvo vangangove vatoziva nezve. dati izvo zvavanochengeta uye, nokudaro, zvinogona kupa ruzivo runobatsira rwechidzidzo chino. Huwandu hwakanangwa hwakaonekwa neongororo yekutanga yenhengo dzese dzeAustralia dzeThe Data Warehousing Institute (Tdwi-aap). Ichi chikamu chinokurukura magadzirirwo echikamu chetsvakiridzo yehumbowo yechidzidzo ichi.

3.4.1. Nzira yekuunganidza dati

Kubva panzira nhatu dzinowanzo shandiswa mukutsvagisa ongororo (kureva tsamba yemibvunzo, kubvunzurudza parunhare uye kubvunzurudza wega) (Nachmias 1976, Fowler 1988, de Vaus 1991), gwaro remibvunzo rakagamuchirwa pachidzidzo ichi. Chikonzero chekutanga chekutora chekupedzisira ndechekuti inogona kusvika kune vanhu vakapararira munzvimbo (Blalock 1970, Nachmias naNachmias 1976, Hwang naLin 1987, de Vaus 1991, Gable 1994). Chechipiri, tsamba yemibvunzo yakakodzera kune vakadzidza zvakanyanya (Fowler 1988). Bvunzurudzo yetsamba yechidzidzo ichi yakanyorerwa kune vanotsigira chirongwa chekuchengetedza data, vatungamiriri uye/kana mamaneja epurojekiti. Chechitatu, mibvunzo yepositi yakakodzera kana rondedzero yakachengeteka yemakero iripo (Salant and Dilman 1994). TDWI, mune iyi nyaya, yakavimbika data warehousing association yakapa tsamba yekutumira yenhengo dzayo dzeAustralia. Imwezve mukana wegwaro remibvunzo yetsamba pamusoro pemibvunzo yerunhare kana kubvunzurudzwa kwemunhu wega nderokuti rinobvumira vanopindura kuti vapindure nemazvo, kunyanya kana vanopindura vachida kubvunza marekodhi kana kukurukura mibvunzo nevamwe vanhu (Fowler 1988).

Chinhu chinokanganisa chinogona kunge chiri nguva inodiwa yekuitisa mibvunzo netsamba. Kazhinji, tsamba yemibvunzo inoitwa nenzira iyi: tsamba dzetsamba, kumirira mhinduro, uye kutumira simbiso (Fowler 1988, Bainbridge 1989). Nokudaro, nguva yose inogona kuva yakareba kudarika nguva inodiwa yekubvunzurudza chiso nechiso kana kubvunzurudzwa kwefoni. Zvisinei, nguva yose inogona kuzivikanwa mberi (Fowler 1988, Descombe 1998). Nguva yakapedzwa kuita mabvunzurudzo ega haigone kuzivikanwa pachine nguva sezvo ichisiyana kubva kubvunzurudzo kuenda kubvunzurudzo (Fowler 1988). Kubvunzurudzwa kwefoni kunogona kukurumidza kudarika tsamba dzemibvunzo uye kubvunzurudzwa kwevanhu pachavo asi inogona kuva nehuwandu husina kupindurwa nekuda kwekusavapo kwevamwe vanhu (Fowler 1988). Pamusoro pezvo, kubvunzurudzwa kwefoni kunowanzo kuganhurirwa kune mapfupi rondedzero yemibvunzo (Bainbridge 1989).

Imwe kushaya simba kwegwaro remibvunzo yakatumirwa ndero yepamusoro isiri-mhinduro (Fowler 1988, Bainbridge 1989, Neuman 1994). Nekudaro, matanho akatorwa nekubatanidza chidzidzo ichi neakavimbika data warehousing institution (kureva TDWI) (Bainbridge 1989, Neuman 1994), iyo inopa tsamba mbiri dzechiyeuchidzo kune vasina kupindura (Fowler 1988, Neuman 1994) uye inosanganisirawo imwe tsamba inotsanangura. chinangwa chekudzidza (Neuman 1994).

3.4.2. Analysis unit

Chinangwa chechidzidzo ichi ndechekuwana ruzivo pamusoro pekushandiswa kwekuchengetedza data uye kushandiswa kwayo mukati memasangano eAustralia. Huwandu hwevanhu vanotarisirwa masangano ese eAustralia akaita, kana ari kuita, i deta rekuchengeta. Masangano ega ega anobva anyoreswa. Gwaro remibvunzo rakatumirwa kumasangano anofarira kutora deta rekuchengeta. Iyi nzira inovimbisa kuti ruzivo rwakaunganidzwa runobva kune zvakakosha zvesangano rega rega riri kutora chikamu.

3.4.3. Survey muenzaniso

Rondedzero yetsamba yevakapinda muongororo yakawanikwa kubva kuTDWI. Kubva pane iyi runyorwa, 3000 masangano eAustralia akasarudzwa sehwaro hwesampling. Tsamba yekutevera inotsanangura purojekiti uye chinangwa cheongororo, pamwe chete nefomu remhinduro uye envelopu yeprepaid yekudzosera gwaro remibvunzo rakapedzwa zvakatumirwa kumuenzaniso. Pamasangano zviuru zvitatu, 3000 akabvuma kupinda muchidzidzo ichi. Nhamba shoma yakadaro yemhinduro yaitarisirwa dato huwandu hukuru hwemasangano eAustralia akange atambira kana kumbundira zano rekuchengetedza data mukati memasangano avo. Nekudaro, vanhu vanonangwa pachidzidzo ichi vane masangano zana nemakumi mapfumbamwe nemasere chete.

3.4.4. Zviri mukati mebvunzo

Magadzirirwo emibvunzo yakavakirwa paMonash data warehousing modhi (yakakurukurwa kare muchikamu 2.3). Zviri mugwaro remibvunzo zvaibva paongororo yezvinyorwa yakapihwa muchitsauko 2. Kopi yemibvunzo yakatumirwa kune vatori vechikamu muongororo inogona kuwanikwa muAppendikisi B. Bvunzurudzo inoumbwa nezvikamu zvitanhatu, izvo zvinotevera matanho emuenzaniso wakavharwa. Ndima nhanhatu dzinotevera dzinopfupikisa muchidimbu zviri muchikamu chimwe nechimwe.

Chikamu A: Ruzivo rwekutanga nezvesangano
Chikamu chino chine mibvunzo inechekuita nenhoroondo yemasangano ari kutora chikamu. Pamusoro pezvo, mimwe yemibvunzo ine chekuita nechimiro chemutori wechikamu chekuchengetedza data. Mashoko akavanzika akadai sezita resangano haana kuburitswa muongororo yeongororo.

Chikamu B: Tanga
Mibvunzo iri muchikamu chino ine chekuita nekutanga pakuchengetedza data. Mibvunzo yakabvunzwa maererano nevatangi veprojekiti, vatsigiri, hunyanzvi hunodiwa uye ruzivo, zvinangwa zvekuvandudza kwekuchengetedza data uye zvinotarisirwa nevashandisi vekupedzisira.

Chikamu C: Dhizaini
Ichi chikamu chine mibvunzo ine chekuita nekuronga zviitiko zve deta rekuchengeta. Kunyanya, mibvunzo yaiva pamusoro pehuwandu hwekushandiswa, nguva yeprojekti, mari yeprojekti uye kuongororwa kwemari / kubatsirwa.

Chikamu D: Kubudirira
Muchikamu chekusimudzira pane mibvunzo ine chekuita nemabasa ekusimudzira e deta rekuchengeta: muunganidzwa wezvinodiwa mushandisi wekupedzisira, masosi e dati, muenzaniso une musoro we dati, prototypes, kuronga kugona, hunyanzvi hwekuvaka uye kusarudzwa kwedhata warehousing maturusi ekuvandudza.

Chikamu E: Kushanda
Mibvunzo yekushandisa ine chekuita nekushanda uye kuwedzera kweiyo deta rekuchengeta, sezvainoshanduka muchikamu chinotevera chebudiriro. Ikoko mhando ye data, maitiro ekuvandudza e dati, granularity ye dati, scalability ye deta rekuchengeta uye nyaya dzekuchengetedza deta rekuchengeta yaiva pakati pemhando dzemibvunzo yaibvunzwa.

Chikamu F: Budiriro
Ichi chikamu chine mibvunzo ine chekuita nekushandisa iyo deta rekuchengeta nevashandisi vekupedzisira. Muongorori aifarira chinangwa uye kushandiswa kweiyo deta rekuchengeta, ongororo uye nzira dzekudzidzisa dzakagamuchirwa uye nzira yekudzora ye deta rekuchengeta kugamuchirwa.

3.4.5. Response rate

Kunyange zvazvo tsvakurudzo dzetsamba dzichitsoropodzwa nekuda kwekuva nehuwandu hwekupindura, matanho akatorwa kuti awedzere chiyero chekudzoka (sezvakurukurwa pamusoro apa muchikamu 3.4.1). Izwi rekuti 'response rate' rinoreva huwandu hwevanhu mune imwe ongororo sample vanopindura mubvunzo (Denscombe 1998). Iyi fomula inotevera yakashandiswa kuverenga mwero wemhinduro yechidzidzo ichi:

Nhamba yevanhu vakapindura
Response rate = ——————————————————————————— X 100 Nhamba yose yemibvunzo yakatumirwa

3.4.6. Test Pilot

Bvunzo risati ratumirwa kumuenzaniso, mibvunzo yakaedzwa nekuita bvunzo dzemutyairi, sezvakakurudzirwa naLuck and Rubin (1987), Jackson (1988), uye de Vaus (1991). Chinangwa chemiyedzo yevatyairi ndechekuburitsa chero matauriro asina kujeka, asina kujeka uye mibvunzo yakaoma-kududzira, kujekesa chero tsananguro uye mazwi anoshandiswa, uye kuona nguva yakatarwa inodiwa kupedzisa gwaro remibvunzo (Warwick naLininger 1975, Jackson 1988, Salant. uye Dilman 1994). Miedzo yekutyaira yakaitwa nekusarudza zvidzidzo zvine maitiro akafanana neaya ezvidzidzo zvekupedzisira, sezvakataurwa naDavis e. Cosenza (1993). Muchidzidzo ichi, nyanzvi nhanhatu dzekuchengetedza dhata dzakasarudzwa sevaridzi vezvidzidzo. Pashure pokuedzwa kwomutyairi mumwe nomumwe, kururamiswa kwaidikanwa kwakaitwa. Kubva pakuedzwa kwemutyairi kwakaitwa, vatori vechikamu vakabatsira pakugadzirisa nekugadzirisa zvakare shanduro yekupedzisira yemibvunzo.

3.4.7. Nzira dzekuongorora dze Dati

I dati Data yeongororo yakaunganidzwa kubva mumibvunzo yakavharwa yakaongororwa pachishandiswa statistical software package inonzi SPSS. Dzakawanda dzemhinduro dzakaongororwa pachishandiswa nhamba dzinotsanangura. Nhamba yemibvunzo yakadzoka isina kukwana. Aya akabatwa zvakanyanya kuti ave nechokwadi chekuti i dati kushaikwa kwaisava mhedzisiro yekukanganisa kwekupinda data, asi nekuti mibvunzo yaive isina kukodzera kune akanyoresa, kana munyoreri akasarudza kusapindura mumwe kana mimwe mibvunzo chaiyo. Idzi mhinduro dzakashaikwa hadzina kufuratirwa pakupeta data dati uye dzakanyorwa se'-9' kuti ive nechokwadi chekubviswa kwavo kubva mukuongororwa.

Mukugadzirira gwaro remibvunzo, mibvunzo yakavharwa yakanyorwa kare nekupa nhamba kune imwe neimwe sarudzo. Nhamba yacho yakabva yashandiswa kudzidzisa i dati panguva yekuongorora (Denscombe 1998, Sapsford naJupp 1996). Semuenzaniso, pakanga paine sarudzo nhanhatu dzakanyorwa mumubvunzo 1 wechikamu B: board of directors, senior executive, IT department, business unit, consultants nevamwe. Mufaira re dati yeSPSS, musiyano wakagadzirirwa 'muvambi weprojekiti', uine mavara matanhatu akakosha: '1' ye'bhodhi revatungamiriri', '2' ye'mukuru mukuru' uye zvichingodaro paMugwagwa. Kushandiswa kwechiyero cheLikertin mune mimwe yemibvunzo yakavharwa kwakabvumirawo kusashanda kuzivikanwa nekushandisa iwo anowirirana manhamba akaiswa muSPSS. Pamibvunzo ine mhinduro dzisina kuperera, dzanga dzisina kupindirana, sarudzo yega yega yaitorwa sechinhu chimwe chete chine mavara maviri akakosha: '1' ye'checked' uye '2' 'ye' isina kutariswa'.

Mibvunzo yakavhurika yakabatwa zvakasiyana nemibvunzo yakavharwa. Mhinduro dzemibvunzo iyi hadzina kuiswa muSPSS. Pane kudaro, vakaongororwa nemaoko. Kushandiswa kwemhando iyi yemubvunzo kunobvumira kuwana ruzivo pamusoro pemafungiro akasununguka uye zvakaitika kune avo vakapindura (Bainbridge 1989, Denscombe 1998). Pazvaibvira, kukamurwa kwemhinduro kwakaitwa.

Zvekuongororwa kwe datinzira dzekuongorora nhamba dzakareruka dzinoshandiswa, senge kuwanda kwemhinduro, zvinorehwa, kutsauka kwakajairwa uye yepakati (Argyrous 1996, Denscombe 1998).
Muedzo weGamma wakaita basa rekuwana zviyero zvehuwandu hwemasangano pakati dati ordinals (Norusis 1983, Argyrous 1996). Miedzo iyi yaive yakakodzera nekuti zviyero zvakashandiswa zvakange zvisina zvikamu zvakawanda uye zvaigona kuratidzwa patafura (Norusis 1983).

3.5 Pfupiso

Muchikamu chino, nzira yetsvakiridzo nemagadzirirwo akatorwa pachidzidzo ichi zvakakurukurwa.

Kusarudza nzira yakanyatsokodzera yekutsvagisa yeimwe chidzidzo kunotora
kutariswa kwemitemo yakati wandei, kusanganisira chimiro uye rudzi rwekutsvagisa, pamwe nekukodzera uye kusasimba kweimwe neimwe nzira inogoneka (Jenkins 1985, Benbasat et al. 1097, Galliers uye Land 1987, yin 1989, Hamilton uye ives 1992, Galliers 1992, neuman 1994). Nekuda kwekushaikwa kweruzivo rwuripo uye dzidziso maererano nekutorwa kwekuchengetwa kwedata muAustralia, chidzidzo chetsvakiridzo ichi chinoda nzira yetsvakiridzo yekududzira ine kugona kuongorora kuongorora zviitiko zvemasangano eAustralia. Iyo yakasarudzwa yekutsvagisa nzira yakasarudzwa kuti iunganidze ruzivo nezve kutorwa kweiyo data ware-housing pfungwa nemasangano eAustralia. Gwaro remibvunzo yeposita rakasarudzwa senzira yekuunganidza dati. Zvikonzero zvenzira yekutsvagisa uye nzira yekuunganidza dati sarudzo dzichapihwa muchitsauko chino. Pamusoro pazvo, nhaurirano yakauyiswa pamusoro pechikamu chekuongorora, muenzaniso wakashandiswa, zvikamu zvemhinduro, zviri mugwaro remibvunzo, pre-bvunzo yebvunzo uye nzira yekuongorora. dati.

Kugadzira a Dhata Warehouse:

Kubatanidza Entity Hukama uye Dimensional Modelling

KUTANGA
Store i dati inyaya huru iripo kumasangano mazhinji. Dambudziko rakakosha mukuvandudza kwekuchengetedza dati ndiwo magadzirirwo ake.
Iyo dhizaini inofanirwa kutsigira kuwanikwa kwemaconcepts mune deta rekuchengeta kune legacy system uye mamwe masosi e dati uye zvakare kunzwisisa kuri nyore uye kugona mukuita kwe deta rekuchengeta.
Mazhinji emabhuku ekuchengetera zvinhu dati inokurudzira kushandiswa kwe entity relationship modelling kana dimensional modelling kumiririra dhizaini ye deta rekuchengeta.
Mupepa rino tinoratidza kuti zvose zvinomiririra zvinogona kusanganiswa sei nenzira yekugadzirwa kwe deta rekuchengeta. Nzira inoshandiswa yakarongeka

inoongororwa mune imwe nyaya uye inotaridzwa mune dzinoverengeka zvakakosha zvinorehwa nenyanzvi.

DATA WAREHOUSSING

Un deta rekuchengeta rinowanzotsanangurwa se "chidzidzo-chakatarisana, chakabatanidzwa, chakasiyana-siyana, uye chisingachinji chekuunganidza data mukutsigira zvisarudzo zvemaneja" (Inmon naHackathorn, 1994). Nyaya-yakatarisana uye yakabatanidzwa inoratidza kuti iyo deta rekuchengeta yakagadzirirwa kuyambuka miganhu inoshanda yenhaka masisitimu kuti ipe maonero akabatanidzwa e dati.
Nguva-yakasiyana ine chekuita nenhoroondo kana nguva-yakatevedzana chimiro chevhidhiyo dati mu deta rekuchengeta, iyo inogonesa maitiro kuti aongororwe. Non-volatile inoratidza kuti deta rekuchengeta haisi kuramba ichivandudzwa sea Database ye OLTP. Asi inovandudzwa nguva nenguva, ne dati kubva mukati nekunze zvinyorwa. The deta rekuchengeta yakanyatsogadzirirwa kutsvagisa kwete kunatsurudza kuvimbika uye kushanda kwekuita.
Pfungwa yekuchengetedza i dati hachisi chitsva, chaive chimwe chezvinangwa zvekutungamira dati kubvira makumi matanhatu (Il Martin, 1982).
I deta rekuchengeta vanopa zvivakwa dati kune manejimendi anotsigira masisitimu. Masisitimu ekutsigira manejimendi anosanganisira sarudzo dzekutsigira masisitimu (DSS) uye Executive information masisitimu (EIS). A DSS icomputer-based information system yakagadzirirwa kuvandudza maitiro uye nekudaro kuita sarudzo dzevanhu. An EIS kazhinji inzira yekutumira dati iyo inoita kuti vatungamiri vebhizimisi vakwanise kuwana maonero e dati.
Iyo general architecture ye deta rekuchengeta inoburitsa basa re deta rekuchengeta mukutsigira manejimendi. Pamusoro pekupa zvivakwa dati yeEIS neDSS, al deta rekuchengeta inogona kuwanikwa zvakananga kuburikidza nemibvunzo. THE dati inosanganisirwa mu a deta rekuchengeta zvakavakirwa pakuongorora kweruzivo rwekutarisira ruzivo uye anowanikwa kubva kune matatu masosi: yemukati legacy masisitimu, yakakosha chinangwa chekutora data masisitimu uye ekunze data masosi. THE dati mumasisitimu enhaka yemukati anowanzo kushaya, kusaenderana, kwemhando yakaderera, uye kuchengetwa mune akasiyana mafomati saka anofanirwa kuyananiswa nekucheneswa asati atakurwa mukati.

deta rekuchengeta (Inmon, 1992; McFadden, 1996). THE dati kubva kuhurongwa hwekuchengetedza dati ad hoc uye kubva kunzvimbo dati zvekunze zvinowanzo shandiswa kuwedzera (update, kutsiva) i dati kubva kune legacy systems.

Pane zvikonzero zvakawanda zvinokurudzira kugadzira a deta rekuchengeta, iyo inosanganisira yakagadziridzwa kuita sarudzo kuburikidza nekushandiswa kunobudirira kweruzivo rwakawanda (Ives 1995), rutsigiro rwekutarisa pazvinhu zvese (Graham 1996), uye kuderedzwa kwemitengo yekuita sarudzo. dati yeEIS neDSS (Graham 1996, McFadden 1996).

Ongororo yemazuva ano epirical yakawana, paavhareji, kudzoka pakudyara kwei deta rekuchengeta ne401% mushure memakore matatu (Graham, 1996). Nekudaro, zvimwe zvidzidzo zveempirical zve deta rekuchengeta akawana matambudziko akakosha anosanganisira kuomerwa pakuyera nekugovera mabhenefiti, kushaikwa kwechinangwa chakajeka, kurerutsa chiyero uye kuoma kwemaitiro ekuchengeta. dati, kunyanya maererano nekwakabva uye kuchena kwe dati. Store i dati inogona kutorwa semhinduro kudambudziko rekutarisira dati pakati pemasangano. The manipulation of dati sechishandiso chemagariro chakaramba chiri chimwe chezvinetso zvakakosha mukugadzirisa zvirongwa zvemashoko pasi rose kwemakore akawanda (Brancheau et al. 1996, Galliers et al. 1994, Niederman et al. 1990, Pervan 1993).

Nzira yakakurumbira yekutarisira asset dati mumakore makumi masere kwaive kugadzirwa kwemuenzaniso dati social. Model dati social yakagadzirirwa kupa hwaro hwakasimba hwekuvandudzwa kwemaitiro matsva ekushandisa e Database uye kuvakazve uye kubatanidzwa kwenhaka masisitimu (Brancheau et al.

1989, Goodhue et al. 1988: 1992, Kim naEverest 1994). Zvisinei, pane matambudziko akati wandei nenzira iyi, kunyanya, kuoma uye mutengo webasa rega rega, uye nguva yakareba inodiwa kuti uwane zvinobatika mhedzisiro (Beynon-Davies 1994, Earl 1993, Goodhue et al. 1992, Periasamy 1994, Shanks 1997 )

Il deta rekuchengeta idatabase rakasiyana rinogara pamwe chete nenhoroondo dzenhaka pane kutsiva iwo. Naizvozvo inobvumidza iwe kutungamira manejimendi e dati uye kudzivirira kuvakazve kunodhura kwemaitiro enhaka.

NZIRA IRIPO YEKUGADZIRA DATA

Imba yekuchengetedza

Nzira yekuvaka nekugadzirisa a deta rekuchengeta inofanirwa kunzwisiswa zvakanyanya senzira yekushanduka-shanduka kwete yechinyakare masisitimu ekuvandudza hupenyu (Desire, 1995, Shanks, O'Donnell naArnott 1997a). Pane maitiro akawanda anobatanidzwa muprojekti deta rekuchengeta zvakadai sekutanga, kuronga; ruzivo rwakatorwa kubva kune zvinodiwa zvinokumbirwa kubva kumamaneja ekambani; masosi, shanduko, kuchenesa kwe dati uye sync kubva kunhaka masisitimu uye mamwe masosi dati; zvirongwa zvekuendesa pasi pekuvandudzwa; monitoring ye deta rekuchengeta; uye kusava nemusoro kwegadziriro yemhindumupindu nekuvaka a deta rekuchengeta (Stinchi, O'Donnell naArnott 1997b). Mujenari rino, tinotarisisa nzira yekudhirowa i dati yakachengetwa muchirevo chemamwe maitiro aya. Kune akati wandei emaitiro akarongwa evhidhiyo architecture deta rekuchengeta mumabhuku (Inmon 1994, Ives 1995, Kimball 1994, McFadden 1996). Imwe neimwe yeiyi nzira ine ongororo pfupi nekuongororwa kwesimba ravo uye kushaya simba.

Inmon's (1994) Nzira ye Dhata Warehouse patani

Inmon (1994) akakurudzira matanho mana ekudzokorora kugadzira a deta rekuchengeta (ona Mufananidzo 2). Nhanho yekutanga ndeyekugadzira template dati social kunzwisisa kuti sei i dati inogona kubatanidzwa munzvimbo dzese dzinoshanda mukati mesangano nekugovanisa i dati chitoro munzvimbo. Model dati inogadzirirwa kuchengetedza dati zvine chekuita nekuita sarudzo, kusanganisira dati nhoroondo, uye yakabatanidzwa dati yakabviswa uye yakaunganidzwa. Danho rechipiri nderokuona nzvimbo dzezvidzidzo zvekushandisa. Izvi zvinobva pane zvakakosha zvakatemwa nerimwe sangano. Danho rechitatu rinosanganisira kudhirowa a Database yenzvimbo yezvidzidzo, nyatso tarisa kusanganisa mazinga akakodzera egranularity. Inmon inokurudzira kushandisa chimiro uye hukama modhi. Danho rechina nderekuziva mabviro masisitimu dati inodiwa uye kuvandudza maitiro ekushandura kutora, kuchenesa uye fomati i dati.

Masimba eInmon's approach ndiyo iyo modhi dati social inopa hwaro hwekubatanidzwa kwe dati mukati mesangano nerutsigiro rwekuronga kwekuvandudzwa kwekudzokorora kwe deta rekuchengeta. Kukanganisa kwayo ndiko kuoma uye mari yekugadzira modhi dati zvemagariro, kuomerwa mukunzwisisa mhando dzemasangano uye hukama hunoshandiswa mune ese mamodheru, izvo dati zvemagariro uye izvo zve dati inochengetwa nenzvimbo yenyaya, uye nekukodzera kweiyo dati yekudhirowa kwe deta rekuchengeta zvekugadzira Database zvehukama asi kwete zve Database multi-dimensional.

Ives' (1995) Nzira yeku Dhata Warehouse patani

Ives (1995) anoronga nzira ina-nhanho yekugadzira hurongwa hweruzivo hwaanotenda kuti hunoshanda pakugadzira deta rekuchengeta (ona Mufananidzo 3). Iyo nzira yakavakirwa zvakanyanya paRuzivo Injiniya yekuvandudza masisitimu eruzivo (Martin 1990). Danho rokutanga nderokuona zvinangwa zvako, kubudirira uye zvinhu zvakakosha, uye zviratidzo zvekuita zvakakosha. Makiyi ebhizinesi maitiro uye ruzivo rwakakosha runoteedzerwa kutitungamira kune modhi dati social. Danho rechipiri rinosanganisira kugadzira architecture inotsanangura dati kuchengetwa nenzvimbo, Database di deta rekuchengeta, iyo tekinoroji zvikamu zvinodikanwa, seti yerutsigiro yesangano inodiwa kuita uye kushanda nayo deta rekuchengeta. Nhanho yechitatu inosanganisira kusarudzwa kwevanodiwa software mapakeji uye maturusi. Danho rechina ndiro rakadzama dhizaini nekuvakwa kwe deta rekuchengeta. Ives anoti chitoro ichocho dati inzira inomanikidzirwa yekudzokorora.

Kusimba kweiyo nzira yeIves ndiko kushandiswa kwehunyanzvi hwekutemerwa kuona zvinodiwa zveruzivo, kushandiswa kwemaitiro akarongeka kutsigira kubatanidzwa kwe. deta rekuchengeta, iyo yakakodzera hardware uye software sarudzo, uye kushandiswa kwemaitiro akawanda ekumiririra e deta rekuchengeta. Kukanganisa kwaro kwakazvarwa mukuoma kunzwisisa. Zvimwe zvinosanganisira kuomerwa nekugadzira mazinga akawanda e Database all'interno del deta rekuchengeta munguva yakafanira uye mutengo.

Kimball's (1994) Nzira ye Dhata Warehouse patani

Kimball (1994) akakurudzira matanho mashanu ekudzokorora ekugadzira a deta rekuchengeta (ona Mifananidzo 4). Maitiro ake anonyanya kutsaurirwa pakudhirowa kwe solo deta rekuchengeta uye pamashandisirwo emhando dzemadimensional pachinzvimbo kune mubatanidzwa uye mhando dzehukama. Kimball anoongorora iwo emhando dzemhando nekuti zviri nyore kuti vatungamiriri vebhizinesi vanzwisise bhizinesi, inoshanda zvakanyanya pakubata nekubvunzana kwakaoma, uye dhizaini Database muviri unoshanda zvakanyanya (Kimball 1994). Kimball anobvuma kuti kugadzira a deta rekuchengeta inodzokorora, uye izvo deta rekuchengeta yakaparadzaniswa inogona kubatanidzwa kuburikidza nekuparadzanisa mumatafura ezviyero zvakafanana.

Danho rekutanga nderokuona imwe nyaya yenyaya kuti ikwane. Nhanho yechipiri neyechitatu inosanganisira kuumbwa kwedimensional. Muchinhanho chechipiri matanho anoona zvinhu zvinofarirwa munzvimbo yezvidzidzo uye kuzvibatanidza mutafura yechokwadi. Semuenzaniso, mune imwe nyaya yekutengesa zviyero zvekufarira zvinogona kusanganisira huwandu hwezvinhu zvinotengeswa uye dhora semari yekutengesa. Danho rechitatu rinosanganisira kuona mativi ayo ari nzira idzo chokwadi chinogona kuiswa mumapoka. Munzvimbo yekutengesa, zviyero zvakakodzera zvinogona kusanganisira chinhu, nzvimbo, uye nguva. Iyo tafura yechokwadi ine akawanda-zvikamu kiyi yekuibatanidza kune yega yega tafura yematafura uye kazhinji ine nhamba yakakura kwazvo yechokwadi. Kusiyana neizvi, matafura ezviyero ane ruzivo rwekutsanangura pamusoro pezviyero uye humwe hunhu hunogona kushandiswa kuunganidza chokwadi. Iyo yakatsanangurwa yakabatana chokwadi uye dimension tafura inoumba inonzi nyeredzi schema nekuda kwechimiro chayo. Danho rechina rinosanganisira kuvaka a Database multidimensional kuti ikwane pateni yenyeredzi. Danho rekupedzisira nderekuziva masource system dati inodiwa uye kuvandudza maitiro ekushandura kutora, kuchenesa uye fomati i dati.

Kusimba kwemaitiro aKimball anosanganisira kushandiswa kwemhando dzemhando kumiririra i dati zvakachengetwa izvo zvinoita kuti zvive nyore kunzwisisa uye zvinotungamira kune inoshanda dhizaini yemuviri. A dimensional modhi iyo zvakare inoshandisa zviri nyore masisitimu Database hukama hunogona kukwaniswa kana masisitimu Database multidimensional. Kukanganisa kwayo kunosanganisira kushaikwa kwemamwe maitiro ekufambisa kuronga kana kubatanidzwa kwezvirongwa zvakawanda zvenyeredzi mukati mea deta rekuchengeta uye kuoma kwekugadzira kubva kune yakanyanyisa denormalized chimiro mudimensional modhi a dati mumasisitimu enhaka.

McFadden's (1996) Nzira yeData Warehouse Dhizaini

McFadden (1996) anopa nzira yenhanho shanu yekudhirowa a deta rekuchengeta (ona Mufananidzo 5).
Maonero ake anobva pamubatanidzwa wemazano kubva muzvinyorwa uye anonangana nekugadzirwa kwechimwe chete deta rekuchengeta. Danho rokutanga rinosanganisira kuongorora zvinodiwa. Nepo tekinoroji yakatarwa isina kunyorerwa, zvinyorwa zveMcFadden zvinozivisa masangano dati kutsanangurwa uye hunhu hwavo, uye inoreva vaverengi Watson naFrolick (1993) kuti vatore zvinodiwa.
Padanho rechipiri, modhi yehukama hwesangano inodhirowewa deta rekuchengeta zvobva zvasimbiswa nevakuru vekambani. Danho rechitatu rinosanganisira kuona mamepu kubva kumasisitimu enhaka uye kwekunze kwe deta rekuchengeta. Nhanho yechina inosanganisira maitiro ekugadzira, kutumira uye kuwiriranisa dati nel deta rekuchengeta. Muchikamu chekupedzisira, kuendeswa kwehurongwa kunogadzirwa nekusimbisa kune mushandisi interface. McFadden anocherekedza kuti maitiro ekudhirowa anowanzo dzokorora.

Kusimba kwemaitiro aMcFadden kubatanidzwa kwevatungamiriri vebhizinesi mukuona zvinodiwa pamwe nekukosha kwezviwanikwa. datikuchenesa uye kuunganidza kwavo. Kukanganisa kwayo kushaikwa kwemaitiro ekuparadzanisa chirongwa chikuru deta rekuchengeta mumatanho akawanda akabatanidzwa, uye ipapo

kuomerwa nekunzwisisa mubatanidzwa uye mhando dzehukama dzakashandiswa mukugadzira deta rekuchengeta.

Havasi ivo chete vari padyo nesu vanotisarudza.