Pūnaewele Pūnaewele Pūnaewele hana me nā ʻenehana o ʻike nui ʻo ka analytics ʻike nui loea, a laila Pūnaewele Pūnaewele Pūnaewele ʻike nui ʻo ia BigʻIkepili Technology.
Pūnaewele Pūnaewele Pūnaewele hāʻawi i nā lawelawe o ʻike nui kālailai, ʻenehana o ʻike nui kālailai, hoʻolālā o ʻike nui kālailai a Monza.
Ke hana nei mākou ʻike nui analytics a hana pū mākou ma ka noiʻi a me ka hoʻomohala ʻana i nā ʻenehana o ʻike nui ʻikepili ma nā kaona penei: Agrate Brianza, Aicurtius, Albiate, Arcore, Barlassina, Bellusco, Bernareggio, Besana ma Brianza, Biassono, Bovisio-Masciago, ʻO Briosco, Brugherio, Burago ma Molgora, Camparada, Aloha Brianza, Carnate, Cavenago ma Brianza, Ceriano Laghetto, Cesano Maderno, Hopu, concorezzo, Correzzana, Makemake, Giussano, Lazzate, Lesmo, Limbiate, Lissone, Macherio, Awelika, Mezzago, kuhi hewa, Monza, Ua make ʻo ia, Nova Milanese, ʻO Ornago, Hana hou, Ronco Briantino, ʻO Seregno, Seveso, Sovico, Sulbiate, Triuggio, Usmate Velate, ʻO Varedo, ʻIke lākou iā al Lambro, ʻO Veduggio me Colzano, ʻO Verano Brianza, Villasanta, Vimercate.
E hana kākou i kāu papahana o ʻike nui analytics a ʻaʻole mākou e haʻalele iā ʻoe.
Pūnaewele Pūnaewele Pūnaewele hāʻawi i ka ʻōlelo aʻoaʻo hoʻolālā, ʻikeʻikepili, papahana na ʻike nui, kālailai i ʻike nui i hōʻiliʻili ʻia e ka ʻoihana, hoʻoulu ʻikepili a me ka waihona ʻana, ka hana ʻana dati, kālailai dati, ʻike kiʻi dati, loea helu, i dati ua kālailai ʻia e nā poʻe loea, ʻike ʻike, ʻike ʻike ʻike, ʻike nui: ke kūkākūkā a me nā noi a me nā pono hana, dbms, hōkeoʻikepili ʻōnaehana hoʻokele, hale kūʻaiʻikepili, hoʻopiha piha ʻike nui, ʻikepili wānana, ʻikepili kiʻekiʻe, alakaʻi ʻia i ka ʻikepili, lā wehe, ka maikaʻi o ka ʻikepili, ʻepekema data, ka maikaʻi o ka ʻikepili.
Aia ʻoe i ka paʻakikī?
Ke nalowale nei ʻoe i ka hoʻokūkū?
Makemake ʻoe i ka hoʻokō ʻana a me ka mālama ʻana i ke kumukūʻai?
Hoʻolilo mākou i ka manawa a me ke kālā i ka noiʻi a me ka hoʻomohala ʻana no nā ʻenehana o ʻike nui hoʻokoliona.
He hui kūikawā mākou i ka hoʻolālā a me ka hoʻokō ʻana i nā hoʻonā hou i nā ʻāpana Digital Services a me Technology. Hana mākou i ka noiʻi a me ka hoʻomohala ʻana no nā ʻenehana o ʻike nui hoʻokoliona.
Hoʻolālā, hoʻokō, mālama ʻana, ʻae i kā mākou nā mea kūʻai mai e hoʻokō i nā pahuhopu i hoʻonohonoho ʻia no nā ʻenehana o ʻike nui hoʻokoliona.
Hoʻohālike mākou i kāu ʻoihana e like me kāu makemake a hahai mākou iā ʻoe ma 360 kekelē.
In Pūnaewele Pūnaewele Pūnaewele hana mākou i kāu mau kaʻina hana ʻoihana maoli i nā ʻenehana hou o ʻike nui hoʻokoliona.
Aia ʻoe i ka paʻakikī?
Ke nalowale nei ʻoe i ka hoʻokūkū?
Makemake ʻoe i ka hoʻokō ʻana a me ka mālama ʻana i ke kumukūʻai?
Pūnaewele Pūnaewele Pūnaewele hāʻawi i ka ʻōlelo aʻoaʻo hoʻolālā, ʻikeʻikepili, papahana na BigʻIkepili Kālailai, kālailai i BigʻIkepili i hōʻiliʻili ʻia e ka ʻoihana, hoʻoulu ʻikepili a me ka waihona ʻana, ka hana ʻana dati, kālailai dati, ʻike kiʻi dati, loea helu, i dati ua kālailai ʻia e nā poʻe loea, ʻike ʻike, ʻike ʻike ʻike, ʻike nui kālailai: ke kūkākūkā a me nā noi a me nā pono hana, dbms, hōkeoʻikepili ʻōnaehana hoʻokele, hale kūʻaiʻikepili, hoʻopiha piha Nuiʻike ʻikepili, ʻikepili wānana, ʻikepili kiʻekiʻe, alakaʻi i ka ʻikepili, lā wehe, ka maikaʻi o ka ʻikepili, ʻepekema data, ka maikaʻi o ka ʻikepili. 'Ipekemaʻikepili. Hoʻonaʻauaoʻikepili. Nuiʻike. Nuiʻike hoʻokoliona. Nuiʻike mea kālailai. Nuiʻike ʻikepili. Nuiʻike kālailai e ʻike nui kālailai. Nā ʻenehana o ʻike nui. Nā papahana e ʻike nui. ʻIke ʻikepili. Kipaku ʻikepili. BigʻIkepili e aʻo aʻo. Nuiʻike a me ka mining mining. ʻEli ʻikepili. ʻIke ʻikeʻikeʻikeʻikeʻikeʻikeʻike. Kūkākūkā ʻike nui. ʻŌlelo aʻo ʻikeʻikepili. Nuiʻike ʻauhau. Wehe i ka ʻikepili. E wehe ʻIkeʻIkeʻIkepili. Nui Wehe i ka ʻikepili. Ke hana nei mākou BigʻIkepili a manaʻo mākou iā mākou iho he Nui ʻIkeʻIkeʻIkepili. Ke hana nei mākou BigʻIkepili a me ka Kaʻikepiliʻikepili. Hana mākou me ka Ka ʻikepili ʻikepili.Kūkākūkā hoʻolālā, ʻikeʻikepili, papahana na ʻike nui, kālailai i ʻike nui i hōʻiliʻili ʻia e ka ʻoihana, hoʻoulu ʻikepili a me ka waihona ʻana, ka hana ʻana dati, kālailai dati, ʻike kiʻi dati, loea helu, i dati ua kālailai ʻia e nā poʻe loea, ʻike ʻike, ʻike ʻike ʻike, ʻike nui: ke kūkākūkā a me nā noi a me nā pono hana, dbms, hōkeoʻikepili ʻōnaehana hoʻokele, hale kūʻaiʻikepili, hoʻopiha piha ʻike nui, ʻikepili wānana, ʻikepili kiʻekiʻe, alakaʻi ʻia i ka ʻikepili, lā wehe, ka maikaʻi o ka ʻikepili, ʻepekema data, ka maikaʻi o ka ʻikepili.
Aia ʻoe i ka paʻakikī?
Ke nalowale nei ʻoe i ka hoʻokūkū?
Makemake ʻoe i ka hoʻokō ʻana a me ka mālama ʻana i ke kumukūʻai?
Pūnaewele Pūnaewele Pūnaewele, hana e like Pūnaewele Pūnaewele e ʻoihana hoʻolaha pūnaewele e Pūnaewele Pūnaewele, e hana pūnaewele ed e-kalepa, ke hāʻawi pū nei i nā lawelawe o i hoʻokomo ' pūnaewele e i hoʻokomo ' e-kalepa. ʻO mākou hoʻokahi Pūnaewele Pūnaewele e hookahi ʻoihana hoʻolaha pūnaewele, ua wehewehe mākou i kāu Pūnaewele Pūnaewele no ka lawelawe o kā mākou lawelawe pono ʻia i ka mea kūʻai hope, hana mākou e like me Hale Pūnaewele , Pūnaehana Pūnaewele , ʻOihana hoʻomohala polokalamu, ʻoihana hoʻolaha pūnaewele, Pūnaewele Pūnaewele e Pūnaewele Pūnaewele. Ua like mākou ʻIkeʻIkeʻIkepili a makemake mākou e hana dati.
Aia ʻoe i ka paʻakikī?
Ke nalowale nei ʻoe i ka hoʻokūkū?
Makemake ʻoe i ka hoʻokō ʻana a me ka mālama ʻana i ke kumukūʻai?
Pūnaewele Pūnaewele Pūnaewele hana ʻo ia me ka ʻike, ʻo ia ke kāne a me ka mīkini a ʻaʻole ke kāne i ka mīkini.
Pūnaewele Pūnaewele Pūnaewele hāʻawi i nā lawelawe o ʻike kūlohelohe a me nā ʻenehana aʻo mīkini, ʻenehana o ʻike kūlohelohe a me nā ʻenehana aʻo mīkini, hoʻolālā o ʻike kūlohelohe a me nā ʻenehana aʻo mīkini.
Pūnaewele Pūnaewele Pūnaewele hana ma nā kumuhana aʻe: Kapua Kamepiula, ʻO Quantum Pūnaewele, ʻimi hoʻopunipuni manao, Ka Papa Hana, Hoʻonui augmented, ʻOiaʻiʻoʻoiaʻiʻo, ʻOihana hana e Hoʻokūkū Lopaka, Internet o na mea.
Hoʻopukapuka mākou i ka manawa a me ke kālā i ka noiʻi a me ka hoʻomohala ʻana i: Kapua Kamepiula, ʻO Quantum Pūnaewele, ʻimi hoʻopunipuni manao, Ka Papa Hana, Hoʻonui augmented, ʻOiaʻiʻoʻoiaʻiʻo, ʻOihana hana e Hoʻokūkū Lopaka, Internet o na mea.
Pūnaewele Pūnaewele Pūnaewele He hui kūikawā i ka hoʻolālā a me ka hoʻokō ʻana i nā hopena hou i nā ʻenehana Digital a me nā ʻenehana. Hana pū mākou ʻike kūlohelohe.
Hoʻolālā, hoʻokō, mālama ʻana, ʻae i kā mākou nā mea kūʻai mai e hoʻokō i nā pahuhopu i hoʻonohonoho ʻia no kaʻike kūlohelohe a me nā ʻenehana aʻo mīkini.
Hoʻohālike mākou i kāu ʻoihana e like me kāu makemake a hahai mākou iā ʻoe ma 360 kekelē.
In Pūnaewele Pūnaewele Pūnaewele hana mākou i kāu ʻōnaehana ʻoihana i maoliʻike kūlohelohe a me nā ʻenehana aʻo mīkini.
Aia ʻoe i ka paʻakikī?
Ke nalowale nei ʻoe i ka hoʻokūkū?
Makemake ʻoe i ka hoʻokō ʻana a me ka mālama ʻana i ke kumukūʻai?
Pūnaewele Pūnaewele Pūnaewele hāʻawi i ka ʻōlelo aʻoaʻo hoʻolālā, ʻikeʻikepili, papahana na ʻike nui, kālailai i ʻike nui i hōʻiliʻili ʻia e ka ʻoihana, hoʻoulu ʻikepili a me ka waihona ʻana, ka hana ʻana dati, kālailai dati, ʻike kiʻi dati, loea helu, i dati ua kālailai ʻia e nā poʻe loea, ʻike ʻike, ʻike ʻike ʻike, ʻike nui : ke kūkākūkā a me nā noi a me nā pono hana, hoʻopihapiha piha ʻike nui, lā wehe, ka maikaʻi o ka ʻikepili, ʻepekema data, ka maikaʻi o ka ʻikepili, ʻikepili wānana, ʻikepili kiʻekiʻe, hoʻokele ʻikepili, wehe ʻepekema data, nui lā wehe, dbms, hōkeoʻikepili ʻōnaehana hoʻokele, hale kūʻaiʻikepili.
E hana kākou i kāu papahana o ʻike nui a ʻaʻole mākou e waiho wale iā ʻoe.
Aia ʻoe i ka paʻakikī?
Ke nalowale nei ʻoe i ka hoʻokūkū?
Makemake ʻoe i ka hoʻokō ʻana a me ka mālama ʻana i ke kumukūʻai?
I dati nā aila o ka millennium hou, i ʻike nui he ʻenehana hōʻino lākou no ka mea ʻoi aku ka nui o ka loli, ʻoi aku ka nui o ka hana hou. Pūnaewele pūnaewele pūnaewele manaoio ka ka maikaʻi o ka ʻikepili ʻo ia ka wā e hiki mai ana, a ua haawiia ʻaʻole ka maikaʻi he kumukūʻai no nā ʻoihana a dati pono e emi mau ke kumu kūʻai o nā huahana.
Pūnaewele Pūnaewele Pūnaewele hana ma dati, a ʻaʻole wale nā mea kokoke iā mākou e koho iā mākou.
I dati i ke ʻano uila i hana nui i ka ʻike a me ka ʻenehana kamaʻilio (ICT) kaiāulu a mahalo i kā lākou hoʻolaha ʻana i ka "maikaʻi" o dati i ka palapala uila a me kona hopena ma nā ʻano hana like ʻole o ke kaiāulu ICT e lilo ana i mea nui.
Ke koʻikoʻi o ka maikaʻi o ka ʻikepili i nā kaʻina hana hoʻoholo i hōʻike ʻia i loko o ka ʻōlelo ʻEulopa Statistics kūlana maikaʻi: "Hāʻawi mākou i ka European Union a me ka honua me ka ʻike kiʻekiʻe e pili ana i ka hoʻokele waiwai a me ke kaiāulu ma ʻEulopa, ka pae ʻāina a me ka pae, a hāʻawi mākou i kēia ʻike i kēlā me kēia. ma ke ʻano he kākoʻo i nā hana hoʻoholo, noiʻi a hoʻopaʻapaʻa. " I ka ka maikaʻi o ka ʻikepili, un ua haawiia ʻaʻole ka maikaʻi he kumukūʻai no nā ʻoihana a dati pono e emi mau ke kumu kūʻai o nā huahana.
ʻO ka Institute Warehousing Institute, i kahi hōʻike 2002 ma ka maikaʻi o ka ʻikepili, hoʻopaʻapaʻa aia he āpau nui ma waena o ka ʻike a me ka ʻoiaʻiʻo o ka maikaʻi o ka ʻikepili i nā hui he nui, a me kēlā mau pilikia e pili ana i ka maikaʻi o ka ʻikepili lilo aku nā ʻoihana US ma mua o $ 600 biliona i kēlā me kēia makahiki, a i loko ka maikaʻi o ka ʻikepili, un ua haawiia ʻaʻole ka maikaʻi he kumukūʻai no nā ʻoihana a dati pono e emi mau ke kumu kūʻai o nā huahana.
I dati i ka palapala uila ʻoi aku ka maikaʻi o kā lākou qualitative ma mua o dati waiho ʻia ma nā palapala pepa, inā ka ka maikaʻi o ka ʻikepili: a ' ua haawiia ʻaʻole ka maikaʻi he kumukūʻai no nā ʻoihana a dati pono e emi mau ke kumu kūʻai o nā huahana.
Pūnaewele Pūnaewele Pūnaewele hana ma Ka ʻikepili ʻikepili kahi, ka pono e hoʻomaopopo a hoʻonā i nā pilikia maikaʻi a no laila e ʻike i nā pane i nā nīnau aʻe: He aha ka ka maikaʻi o ka ʻikepili? ʻO nā ʻenehana, nā hana hana a me nā pilikia kū i ka ka maikaʻi o ka ʻikepili ua hoʻohui ʻia lākou? He aha nā ala kokoke a kaulana loa? He aha nā pilikia i hoʻoponopono ʻole ʻia?
Ua hoʻolaha ʻia nā ʻaha kūkā lehulehu e nā kaiāulu i loaʻa nā kumu o dati a me nā ʻōnaehana ʻike e like me ke kahua nui o ka hoʻokolokolo; ʻo ka paʻi mua o ka International Conference on Information Quality (ICIQ), i hoʻonohonoho maʻamau ʻia ma ka Massachusetts Institute of Technology (MIT) ma Boston, mai ka makahiki 1996; ua kākoʻo ka International Workshop on Information Quality in Information Systems (IQIS) i ka hālāwai SIGMOD mai 2004; ua mālama ʻia ka seminar International Data and Information Quality (DIQ) i loko o ka Conference on Advanced Information Systems Engineering (CAiSE) mai 2004; a ua mālama ʻia ka seminar honua Quality of Information Systems (QoIS), i hui pū me ka Entity Relationship (ER) conference mai 2005. France, Germania a ma Amerika Huipuia.
He leka uila wale mākou, ʻaʻole ʻo ka poʻe kokoke iā mākou e koho iā mākou.
Aia ʻoe i ka paʻakikī?
Ke nalowale nei ʻoe i ka hoʻokūkū?
Makemake ʻoe i ka hoʻokō ʻana a me ka mālama ʻana i ke kumukūʻai?
I dati ʻo ia ka ʻaila o ka mileniuma hou, ka lā wehe he ʻenehana hōʻino lākou no ka mea ʻoi aku ka nui o ka loli, ʻoi aku ka nui o ka hana hou. Pūnaewele pūnaewele pūnaewele manaʻoʻiʻo kēlā lā wehe pololei a hiki i ka wā e hiki mai ana, a ua haawiia ʻaʻole hamama kahi kumukūʻai no nā ʻoihana a dati hamama pono mau ke kumu kūʻai.
Pūnaewele Pūnaewele Pūnaewele hana ma dati, a ʻaʻole wale nā mea kokoke iā mākou e koho iā mākou.
Wehewehe: i dati E hiki i nā aupuni ke loaʻa i kēlā me kēia mea hiki ke hāʻawi ʻia i kēlā me kēia ʻano me ka ʻole o nā kapu kope.
I dati hamama hiki ke hele mai kekahi kumu.
Scenario: I dati hamama paha e hoʻopili i nā kumuwaiwai ʻole palapala e like me ka palapala ʻāina, genome, connectome, nā mea hoʻohui kemika, nā makemakika a me nā hana ʻepekema, dati nā kauka a me ka hana, bioscience a me nā mea ola. Kū pinepine nā pilikia no ka mea he waiwai kālepa kā lākou a i ʻole hiki ke hōʻuluʻulu ʻia i nā hana waiwai. Loaʻa a hoʻohana hou paha o dati ua hoomaluia e na hui, ka lehulehu a me ka pono. Hiki ke hoʻomalu ʻia ma o nā kaohi ʻana, nā laikini, nā kope kope, nā patent, a me nā uku no ke komo a hoʻohana hou ʻia. Kākoʻo o lā wehe hoʻopaʻapaʻa ʻaʻole kūʻē kēia mau kapu i ka pono maʻamau a ʻo kēia mau mea dati pono e hoʻolako ʻia me ka ʻole o nā kapu a me nā koina. Eia kekahi, he mea nui i dati hiki ke hoʻohana hou ʻia me ke koi ʻole ʻana i ka ʻae hou, ʻoiai ʻo nā ʻano o ka hoʻohana hou ʻana (e like me ka hoʻokumu ʻana i nā hana derivative) hiki ke hoʻomalu ʻia e kahi laikini.
Pūnaewele Pūnaewele Pūnaewele hana pū me lākou lā wehe No ke aupuni, ʻimi nā noi aupuni wehe maikaʻi loa e hoʻoikaika i nā kamaʻāina, kōkua i nā ʻoihana liʻiliʻi, a i ʻole e hana i ka waiwai ma kekahi ala maikaʻi a maikaʻi. Ka wehe ana o dati He kīpuka wale ke aupuni ma ke ala e hoʻomaikaʻi ai i ka ʻike, hoʻomaikaʻi ʻana i ke aupuni, a me nā mea kūkulu hale e hoʻoponopono ai i nā pilikia o ka honua maoli.
ʻO nā pahuhopu o ka neʻe Wehe i ka ʻikepili ua like lākou me nā neʻe "Wehe" ʻē aʻe.
ʻO ka wehe ʻana e pili ana i ka loaʻa manuahi ʻana o nā puke naʻauao ma Internet. I kekahi mau hihia, ua komo pū kēia mau mea i nā pūʻulu o dati hāmama, nā laʻana he:
-ʻO ka ʻike hāmama e pili ana i ka hoʻolako ʻana i nā kumuwaiwai i kahi anaina kanaka me ka uku ʻole.
-ʻIke wehe. Kākoʻo ʻo Open Knowledge International i ka wehe ʻana ma waena o nā pilikia me ka, akā ʻaʻole i kaupalena ʻia i nā pilikia o lā wehe. Nā uhi, ʻepekema, mōʻaukala, ʻike ʻāina; uhi ʻia nā mea e like me ke mele, nā kiʻiʻoniʻoni, nā puke; uhi ʻia ke aupuni a me nā ʻike hoʻokele ʻē aʻe. ʻO ka lā wehe ua hoʻokomo ʻia ma lalo o ka Open Knowledge Definition, i kuhikuhi ʻia ma ka protocol Science Commons no ka hoʻokō ʻana i ka dati komo komo.
E pili ana ka ʻepekema puke wehe i ka hoʻohana ʻana i ka manaʻo o Wehe i ka ʻikepili i ka hapa nui o ke kaʻina hana ʻepekema hiki, me nā hoʻokolohua hāʻule ʻole a dati hoʻokolohua paʻakikī.
-ʻO ka polokalamu wehe kumu e pili ana i nā laikini kumu wehe e hiki ai ke hoʻokaʻawale ʻia nā polokalamu kamepiula a hana ʻole maʻamau maʻamau dati.
-E wehe ākea nā kumuwaiwai aʻo a ākea e laikini ʻia nā palapala a me nā pāpāho e pono ai no ke aʻo ʻana, ke aʻo ʻana a me ka loiloi, a me nā hana noiʻi.
-E wehe i ka noiʻi / ʻepekema wehe / dati o ka ʻepekema hāmama (pili ʻepekema wehe) hōʻike i kahi ala e wehe a pili i nā ʻepekema e like me dati, nā hana a me nā pono hana me nā ʻenehana o dati hoʻopili ʻia e hiki ai i ka noiʻi aniani moakaka, hoʻopuka hou ʻia a transdisciplinary.
ʻO ka mantra o ka lā wehe : a ' ua haawiia ʻaʻole hamama kahi kumukūʻai no nā ʻoihana a dati hamama pono mau ke kumu kūʻai.
Aia ʻoe i ka paʻakikī?
Ke nalowale nei ʻoe i ka hoʻokūkū?
Makemake ʻoe i ka hoʻokō ʻana a me ka mālama ʻana i ke kumukūʻai?
Koho i nā lawelawe a Pūnaewele Pūnaewele Pūnaewele a hoʻonui i kāu ʻoihana, kahi ʻoihana ʻokoʻa e hāʻawi i nā lawelawe he nui. Hana pū mākou no ka ulu ʻana o kāu ʻoihana. Hana mākou e like Pūnaewele Pūnaewele e ʻoihana hoʻolaha pūnaewele e Pūnaewele Pūnaewele, e hana pūnaewele ed e-kalepa, ke hāʻawi pū nei i nā lawelawe o i hoʻokomo ' pūnaewele e i hoʻokomo ' e-kalepa. ʻO mākou hoʻokahi Pūnaewele Pūnaewele e hookahi ʻoihana hoʻolaha pūnaewele, ua wehewehe mākou i kāu Pūnaewele Pūnaewele no ka lawelawe o kā mākou lawelawe pono ʻia i ka mea kūʻai hope, hana mākou e like me Hale Pūnaewele, Pūnaehana Pūnaewele, ʻOihana hoʻomohala polokalamu, Pūnaewele Pūnaewele, ʻoihana hoʻolaha pūnaewele e Pūnaewele Pūnaewele e hui kaiaulu.
Aia ʻoe i ka paʻakikī?
Ke nalowale nei ʻoe i ka hoʻokūkū?
Makemake ʻoe i ka hoʻokō ʻana a me ka mālama ʻana i ke kumukūʻai?
E hana kāua ʻikeʻikepili a hoʻolilo mākou i ka manawa a me ke kālā i ka noiʻi a me ka hoʻomohala ʻana no ʻikeʻikepili.
He hui kūikawā mākou i ka hoʻolālā a me ka hoʻokō ʻana i nā hopena hou i nā māla o Digital Services a me Technology.
Hana mākou me ka ʻikeʻikepili.
Hoʻolālā, hoʻokō, mālama ʻana, ʻae i kā mākou nā mea kūʻai mai e hoʻokō i nā pahuhopu i hoʻonohonoho ʻia no ka ʻikeʻikepili.
Hoʻohālike mākou i kāu ʻoihana e like me kāu makemake a hahai mākou iā ʻoe ma 360 kekelē.
In Pūnaewele Pūnaewele Pūnaewele hana mākou i kāu hana ʻoihana i maoli i ka ʻikeʻikepili.
Aia ʻoe i ka paʻakikī?
Ke nalowale nei ʻoe i ka hoʻokūkū?
Makemake ʻoe i ka hoʻokō ʻana a me ka mālama ʻana i ke kumukūʻai?
Hana mākou e like ʻepekema data a hoʻolilo mākou i ka manawa a me ke kālā i ka noiʻi a me ka hoʻomohala ʻana no ʻikeʻikepili.
He hui kūikawā mākou i ka hoʻolālā a me ka hoʻokō ʻana i nā hopena hou i nā māla o Digital Services a me Technology.
Hana mākou me ka ʻikeʻikepili a ʻo mākou nō ʻepekema data.
Hoʻolālā, hoʻokō, mālama ʻana, ʻae i kā mākou nā mea kūʻai mai e hoʻokō i nā pahuhopu i hoʻonohonoho ʻia no ka ʻikeʻikepili.
Hoʻohālike mākou i kāu ʻoihana e like me kāu makemake a hahai mākou iā ʻoe ma 360 kekelē.
In Pūnaewele Pūnaewele Pūnaewele hana mākou i kāu hana ʻoihana i maoli i ka ʻikeʻikepili.
Aia ʻoe i ka paʻakikī?
Ke nalowale nei ʻoe i ka hoʻokūkū?
Makemake ʻoe i ka hoʻokō ʻana a me ka mālama ʻana i ke kumukūʻai?
Hana mākou e like me:
-dba mamao kahi e'ōlelo ai
-dba mamao Pualaniq
-dba mamao IBM DB2
-dba mamao Sapana
-dba mamao Pūnaewele SQL Microsoft
-dba mamao Cassandra
-dba mamao ʻO Mongo DB
-dba mamao Informix
-dba mamao Mea ʻoluʻolu
-dba mamao ʻO Teradata.
I dati ʻo lākou ka aila o ka milenio hou, akā hoʻopukapuka mākou i ka manawa a me ke kālā ka maikaʻi o ka ʻikepili no ke aha a ua haawiia ʻaʻole maikaʻi ka uku i ka ʻoihana a dati pono ke kumu kūʻai o ka waiwai a emi iho. Lama Waihona DBA Mau loea | Lama Waihona DBA Nā lawelawe | Mamao Luna Hoʻoponopono Pūnaewele | Lama Waihona DBA | ʻO Stefano Fantin.
Hoʻopukapuka mākou i ka manawa a me ke kālā i ka noiʻi a me ke kūkulu ʻana e like dba mamao.
Hāʻawi mākou i ka ʻōlelo aʻoaʻo dba mamao.
He hui kūikawā mākou i ka hoʻolālā a me ka hoʻokō ʻana i nā hopena hou i nā māla o Digital Services a me Technology.
Hana mākou e like dba mamao.
Hoʻolālā, hoʻokō, mālama ʻana, ʻae i kā mākou nā mea kūʻai mai e hoʻokō i nā pahuhopu i hoʻonohonoho ʻia no ka dba mamao.
Hoʻohālike mākou i kāu ʻoihana e like me kāu makemake a hahai mākou iā ʻoe ma 360 kekelē.
In Pūnaewele Pūnaewele Pūnaewele hana mākou i kāu hana ʻoihana i maoli i dba mamao, ʻoiai dba mamao poʻe loea. Manaʻo mākou i ka hoʻohou ʻana i kāu mau ʻoihana ʻoihana ma o ka hana ʻana iā lākou i ʻōiwi dba mamao.
Hana mākou e like me:
-mea hoʻomanaʻo luna hoʻomalu hōkeo ʻikepili kahi e'ōlelo ai
-mea hoʻomanaʻo luna hoʻomalu hōkeo ʻikepili Pualaniq
-mea hoʻomanaʻo luna hoʻomalu hōkeo ʻikepili IBM DB2
-mea hoʻomanaʻo luna hoʻomalu hōkeo ʻikepili Sapana
-mea hoʻomanaʻo luna hoʻomalu hōkeo ʻikepili Pūnaewele SQL Microsoft
-mea hoʻomanaʻo luna hoʻomalu hōkeo ʻikepili Cassandra
-mea hoʻomanaʻo luna hoʻomalu hōkeo ʻikepili ʻO Mongo DB
-mea hoʻomanaʻo luna hoʻomalu hōkeo ʻikepili Informix
-mea hoʻomanaʻo luna hoʻomalu hōkeo ʻikepili Mea ʻoluʻolu
-mea hoʻomanaʻo luna hoʻomalu hōkeo ʻikepili ʻO Teradata.
O mākou ʻIkeʻIkeʻIkepili a makemake mākou e hana dati.
ʻAʻole wale nā poʻe kokoke iā mākou e koho iā mākou.
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E ʻike hou aʻe mai ka Pūnaewele Pūnaewele Pūnaewele
E kau inoa no ka loaʻa ʻana o nā ʻatikala hou loa ma ka leka uila.
