Nui nā palapala hōʻoia hōʻoia ʻikepili ma ka pūnaewele akā i kekahi manawa paʻakikī loa ka ʻike ʻana i kekahi o nā mea maikaʻi loa o kēia mau palapala hōʻoia ʻikepili ʻikepili pūnaewele.
ʻO ka ʻikepili ʻikepili kekahi o nā ʻoihana e ulu wikiwiki a makemake nui i kēia mau lā. Hoʻolālā ka ʻoihana noiʻi mākeke ʻo Gartner e hiki i ka hoʻolilo ʻoihana ma ka ʻikepili a me nā hopena analytics e hōʻea i $ 189 biliona ma 2022, mai $ 150 biliona i 2019.
Ma ka makahiki 2025, manaʻo ʻia ka mākeke data nui o ka honua he $103 biliona.
ʻO ka ulu ʻana o ka noi no nā ʻoihana ʻepekema data ʻoi aku ka nui o nā poʻe ma mua o ka lawe ʻana i nā papa ʻikepili ʻikepili pūnaewele. Ma ke ʻano he pōmaikaʻi hou, hāʻawi ka nui o kēia mau papa i kahi palapala hōʻoia a i ʻole ka hōʻoia e kōkua iā ʻoe e kū i waho.
Inā ʻoe e noʻonoʻo nei e lawe i kahi papa hōʻoiaʻiʻo, ua uhi mākou iā ʻoe. Ua hōʻuluʻulu mākou i kahi papa inoa o nā palapala hōʻoia ʻikepili ʻikepili maikaʻi loa ma ka pūnaewele e kōkua iā ʻoe e hoʻomaka. Akā ma mua o kēlā, e hōʻoia mākou aia mākou ma ka ʻaoʻao like.
Table of Contents
He aha ka ʻikepili ikepili?
ʻO ka hana a me ka helu helu helu o nā ʻikepili i loaʻa ke kumuhana o ka ʻikepili ʻikepili. Hoʻokumu ka poʻe loiloi i ka hoʻomohala ʻana i nā ala no ka hopu ʻana, ka hana ʻana, a me ka hoʻonohonoho ʻana i ka ʻikepili i mea e ʻike ai i nā ʻike hiki ke hana no nā pilikia o kēia manawa, a me ka hoʻoholo ʻana i ke ala maikaʻi loa e kamaʻilio ai i kēia ʻike.
ʻO ka ʻōlelo maʻalahi, pili ka ʻikepili a me ka analytics i ka ʻimi ʻana i nā hoʻonā i nā pilikia a mākou i maopopo ʻole ai i nā pane. Hoʻokumu pū ʻia i ka hāʻawi ʻana i nā hopena e hiki ke hopena i nā pōmaikaʻi wikiwiki.
Hoʻopili pū ka ʻikepili ʻikepili i kekahi mau lālā ʻē aʻe o nā ʻikepili nui a me ka nānā ʻana e kōkua i ka hui ʻana o nā kumu ʻikepili ʻokoʻa a me ka ʻike ʻana i nā loulou i ka wā e hoʻomaʻamaʻa ana i nā hopena.
Nā Pōmaikaʻi o ka ʻIkepili ʻIkepili
He nui nā pono o ka ʻikepili nui no nā ʻoihana i kēia lā.
Kōkua ʻikepili ʻikepili i:
- ʻOi aku ka maikaʻi o ka hoʻoholo ʻana,
- Hāʻawi i ka hoʻokele pilikia kūpono,
- Hoʻomaikaʻi i ka ʻike mea kūʻai aku, a
- Hoʻonui i ka waiwai o ka brand.
I ka nānā ʻana i kēia mau pōmaikaʻi, ke ulu nei ka noi no nā poʻe loea akamai i ke kahua o ka ʻikepili ʻikepili.
Manaʻo ʻia kēia mau poʻe loea e loaʻa ʻaʻole wale ka ʻike theoretical akā ke ʻike pono hoʻi e pili ana i ka ʻikepili ʻikepili nui.
No ka hōʻoia ʻana i kēia, ke ʻimi nei nā mea hana i nā moho i hoʻomaʻamaʻa ʻia a i ʻole nā papa hōʻoia e hāʻawi i ka ʻike kūpono i ke kumuhana.
Ma waho aʻe o ka hiki ke kālailai i ka ʻikepili, pono e hiki i kēia poʻe loea ke hana i nā hiʻohiʻona ʻike o kēlā ʻikepili i hiki i nā mea hoʻohana ʻole ʻenehana ke hoʻomaopopo pū. ʻO kēia kahi e pāʻani ai nā mea hana e like me Tableau. Hāʻawi kēia mau mea hana iā ʻoe e hana i nā pakuhi pili, nā pakuhi, nā pakuhi, a me nā papa e haʻi i kahi moʻolelo e pili ana i ka hana o kāu hui ma muli o kāna mau hōʻailona hana nui (KPI).
ʻIkepili ʻIkepili Kūʻē i ka ʻepekema ʻikepili
Kaʻikepiliʻikepili a me Data Analytics pili pū me Big Data, akā ma nā ʻano like ʻole. He huaʻōlelo ākea ka ʻIkepili ʻIkepili e hoʻopili ana i ka ʻikepili ʻikepili a me ka ʻepekema data.
Heluhelu, Heluhelu, kamepiula Science, ʻEpekema ʻIke, Aʻo Mīkini, a me Artificial Intelligence i hoʻokomo ʻia i loko o ka ʻIke ʻIke.
Hoʻohana ʻia ka mining data, inference data, predictive modeling, a me ka hoʻomohala ʻana i ka algorithm aʻo mīkini no ka ʻike ʻana i nā mamana mai nā ʻikepili nui a hoʻololi iā lākou i mau hoʻolālā ʻoihana koʻikoʻi. ʻO ka ʻikepili ʻikepili, ma ka ʻaoʻao ʻē aʻe, pili nui i ka Statistics, Mathematics, a me Statistical Analysis.
ʻIke ʻia ka Data Analytics e hōʻike i nā ʻike kikoʻī i unuhi ʻia, ʻoiai ʻo Data Science e kālele ana i ka wehe ʻana i nā pilina koʻikoʻi ma waena o nā ʻikepili nui.
No ka waiho ʻana i kahi ʻano ʻē aʻe, ʻo Data Analytics kahi ʻāpana o ka Data Science e kālele ana i nā hoʻonā kikoʻī hou aku i nā pilikia i hāpai ʻia e Data Science.
Manaʻo ʻo Data Science e ʻimi i nā pilikia hou a hoihoi i hiki ke kōkua i nā ʻoihana e hana hou. ʻO ka ʻikepili ʻikepili, ma ka ʻaoʻao ʻē aʻe, manaʻo e ʻimi i nā pane i kēia mau nīnau a hoʻoholo pehea e hiki ai ke hoʻokō ʻia i loko o kahi ʻoihana e paipai i ka hana hou ʻana i ka ʻikepili.
Ka papa inoa o nā palapala hōʻoia hōʻoia ʻikepili maikaʻi loa ma ka pūnaewele
Aia ma lalo kahi papa inoa o nā palapala hōʻoia hōʻoia ʻikepili pūnaewele maikaʻi loa:
- SAS Advanced Analytics Professional Certification
- SAS Hoʻopaʻa ʻia i ka ʻikepili Curation Professional
- DASCA: ʻEpekema ʻIkepili Nui
- Ua hōʻoia ʻia ʻo Microsoft: Azure Data Scientist Associate
- IBM Data Science Professional Certificate
- ʻO ka palapala hōʻoia ʻoihana ʻepekema ʻikepili ʻo HarvardX
- Coursera: ʻIkepili ʻEpekema ʻIkepili na John Hopkins University
- ʻO ka papahana EdX Big Data MicroMasters
- Udacity Business Analytics Nanodegree
- ʻIkepili ʻikepili DataCamp ma Excel.
10 ʻO nā palapala hōʻoia ʻikepili ʻikepili maikaʻi loa ma ka pūnaewele
1. SAS Advanced Analytics Professional Certification
He pae kiʻekiʻe kēia palapala ʻepekema ʻikepili hāʻawi ʻia e ka SAS Academy for Data Science, a ua uhi ia i kahi ākea o nā kumuhana e like me nā helu, ʻike ʻike ʻike, logistic regression, Hadoop foundations, data mining, a me nā mea hou aku.
Pono nā haumāna ma kahi o ʻeono mahina o ka ʻike papahana ma mua o ka noi ʻana no ka palapala hōʻoia, aia i ʻeiwa mau papa a me ʻekolu mau hoʻokolohua.
Ma muli o ka pono o ka paepae a me ka nui o ka uhi ʻana i nā kumuhana ʻepekema data, manaʻo ka poʻe he ʻoi loa kēia ka hōʻoia no ka ʻepekema data.
2. SAS Hoʻopaʻa ʻia i ka ʻikepili Curation Professional
No ke kūpono i nā ʻano aʻo like ʻole o ka poʻe komo, hāʻawi ka SAS Big Data Certification i ka hoʻomaʻamaʻa alakaʻi alakaʻi a me nā ʻano e-Learning ponoʻī.
Ma mua o ke kau inoa ʻana, pono e loaʻa i nā haumāna ka ʻike ikaika o ka hoʻolālā ʻana, me nā ʻenehana hoʻoponopono ʻikepili a me SQL.
ʻO nā mea hana hoʻokele data a me Hadoop kekahi o nā kumuhana i uhi ʻia. ʻEhā mau papa aʻo a hoʻokahi wale nō hōʻike i loko o kēia pūʻolo.
ʻO ka palapala hōʻoia Data Curation, e like me nā palapala hōʻoia SAS ʻē aʻe, he lawelawe i kau inoa ʻia e hāʻawi iā ʻoe i ke ao no hoʻokahi makahiki ma mua o kou hoʻololi ʻana.
3. DASCA: ʻEpekema ʻIkepili Nui
ʻO ka Data Science Council of America, a i ʻole DASCA, ke kumu alakaʻi o nā palapala ʻepekema data i ʻike ʻia ma ka honua. ʻO kāna mau hōʻoia SDS (Senior Data Scientist) a me PDS (Principal Data Scientist) i waena o nā mea hanohano loa ma ka honua no nā ʻepekema data. E nānā pehea e lilo i ʻepekema data me ke kēkelē laepua.
Hiki i nā moho mai nā ʻano aʻoaʻo like ʻole, me ka hoʻokele ʻoihana, ke kālā, ka ʻikepili, a me ka ʻenehana, hiki ke hoʻohana i nā papahana hōʻoia hohonu hohonu o ka mea kūʻai aku.
4. Ua hōʻoia ʻia ʻo Microsoft: Azure Data Scientist Associate
Makemake ʻoe e hoʻomaopopo i ka hana ʻana a me ka holo ʻana i nā hana aʻo mīkini? ʻO ka Azure Data Scientist Associate palapala hōʻoia mai Microsoft ka mea no ʻoe.
ʻO ka ʻāpana maikaʻi loa e pili ana i kēia palapala hōʻoia Microsoft ʻo ia ka hiki iā ʻoe ke aʻo no ia me ka hoʻohana ʻana i nā hāmeʻa aʻo a Microsoft, akā naʻe, aia kekahi mau koho i alakaʻi ʻia e nā kumu. Aia ka palapala hōʻoia i nā hoʻonā AI, ka hana ʻōlelo kūlohelohe, a me ke aʻo ʻana i ka mīkini.
5. IBM Data Science Professional Certificate
ʻO ka IBM Data Science Professional Certificate kahi hōʻoia ʻikepili pūnaewele pono. E noʻonoʻo paha nā poʻe moho e hoʻomaka i kā lākou ʻoihana ʻepekema data ʻoihana i ka papahana hōʻoia ʻepekema data hoʻomaka.
Aia ka palapala hōʻoia i ka hoʻomaka ʻana i ka ʻepekema ʻikepili me ka aʻo ʻana i ka mīkini, python, nā mea hana open-source, a me SQL i nā papa ʻeiwa.
Hiki ke hoʻopau ʻia kā lākou mau papa i kou manawa ponoʻī, aʻo nā mea hoʻomohala papa e paipai e hoʻopau iā lākou i ʻekolu mahina.
6. ʻO ka palapala hōʻoia ʻoihana ʻepekema ʻikepili ʻo HarvardX
Hāʻawi ʻo HarvardX i nā ʻano papahana pūnaewele i hoʻolālā ʻia e kōkua i nā polopeka e hoʻomaikaʻi i ke aʻo ʻana a me ke aʻo ʻana ma o ka pā kula a me nā ʻano pūnaewele.
Me ka HarvardX's Data Science Professional Certificate, e aʻo ʻoe i nā kumu ʻepekema ʻikepili e like me R a me ke aʻo ʻana i ka mīkini ma o nā haʻawina hihia honua maoli.
Hāʻawi ka HarvardX data science certification i nā mea noi i ka ʻike a me nā mākaukau e pono ai lākou e hoʻoponopono i nā pilikia ʻikepili ʻikepili honua maoli.
ʻO nā papa ʻeiwa i hoʻopaʻa ʻia i ka hōʻoia ʻepekema ʻikepili ʻoihana e uhi i nā kumuhana e pili ana i ka ʻike maka, ke aʻo ʻana i ka mīkini, ka hoʻihoʻi laina laina, ka hiki, ka hakakā ʻikepili, a me nā mea hou aku.
7. Coursera: ʻIkepili ʻEpekema ʻIkepili na John Hopkins University
ʻO kēia palapala Coursera, hāʻawi ʻia e John Hopkins University, he mea kūpono ia no nā poʻe novice e makemake e aʻo pehea e kūkulu ai i kahi huahana data, e hoʻopuka i nā hopena i hoʻoiho ʻia i ka ʻikepili, a hoʻomaʻamaʻa i ka aʻo ʻana i ka mīkini.
Ma mua o ke komo ʻana, pono e ʻike nā haumāna i ka Python.
He manuahi nā papa, akā ʻo ka poʻe e makemake ana e hōʻoia e uku liʻiliʻi, ʻoiai ʻo ka hapa nui o nā palapala hōʻoia Coursera e hoʻomaka ana ma $50.
8. ʻO ka papahana EdX Big Data MicroMasters
He ʻāpana kēia papa o ka papahana Big Data MicroMasters a e kōkua iā ʻoe e hoʻomaikaʻi i kāu hoʻolālā a me nā mākau makemakika ʻoiai e aʻo ana e pili ana i ka ʻikepili nui.
Ma kēia papa, e aʻo ʻoe pehea e mālama ai, mālama, a kālailai i ka ʻikepili i mea e hoʻoholo ai i nā hoʻoholo ʻoihana ʻoi aku ka maikaʻi ma ka honua kikohoʻe o kēia mau lā.
E aʻo ʻoe pehea e hoʻohana ai i nā ʻenehana e like me Apache Spark a me R, he mau mea hana analytic koʻikoʻi. Hiki iā ʻoe ke hoʻokokoke i nā pilikia ʻepekema data nui me ka noʻonoʻo a me ka hoʻolālā ma ka hopena o kēia papa.
9. Udacity Business Analytics Nanodegree
E ʻike ʻoe i nā mākau ʻikepili koʻikoʻi e hoʻohana ʻia ma nā hana a me nā ʻoihana i kēia papahana. E aʻo ʻoe pehea e hoʻohana ai i ka Excel no ke kālailai ʻana i ka ʻikepili a kūkulu i nā kumu hoʻohālike, SQL i ka nīnau ʻana i ka ʻikepili, a me ka Tableau e hana i nā ʻike ʻike ʻike.
ʻAʻohe koi mua no kēia haʻawina kumu.
Manaʻo ʻo Udacity e loaʻa iā ʻoe ka ʻike kamepiula ma mua a hiki iā ʻoe ke hoʻoiho a hoʻokomo i ka polokalamu i mea e kūleʻa ai.
10. ʻIkepili ʻikepili DataCamp ma Excel
Ma kēia papa, e aʻo ʻoe pehea e hoʻohana ai i nā pōkole kīwī mālama manawa, hoʻololi a hoʻomaʻemaʻe i nā palapala ʻikepili e like me ke kikokikona, nā manawa, a me nā lā, a hana i nā hana loiloi kupanaha a me nā hui kūlana ʻoiai e aʻo ana pehea e hoʻohana ai i nā pōkole mālama manawa.
E haku ʻoe ma luna o 35 mau hana Excel hou, me CONCATENATE, VLOOKUP, a me AVERAGEIF(S), a me ka hana pū me ka ʻikepili Kickstarter honua maoli e loiloi i ka mea e holomua ai ka papahana, ma o ka hana lima.
Nā nīnau i nīnau pinepine ʻia e pili ana i ka Online Data Analytics Online Certificate
He aha ka waiwai o kahi palapala hōʻoia Data Analytics?
Pono ka palapala hōʻoia ʻikepili, ʻAe! inā ʻoe e ʻimi nei i kahi hana ma ka ʻikepili ʻikepili. Hāʻawi ka palapala hōʻoia ʻikepili iā ʻoe i nā mākau a me ka ʻike e pono ai e loaʻa kahi hana ma ke ʻano he ʻikepili ʻikepili.
Hiki paha i ka mea kākau ʻikepili ke hana ma ke kumu kūʻokoʻa?
ʻO Freelancing kekahi o nā koho maikaʻi loa no nā ʻepekema data i kēia lā, no nā mea hou a me nā loea. Ma ke ʻano he freelancer ʻepekema data, loaʻa iā ʻoe ka maʻalahi o ke koho ʻana i ka papahana, ka hoʻokele manawa, a me ka uku. He koho maikaʻi loa ia no ka poʻe hoʻomaka e makemake e loaʻa i ka ʻike lima ma ka hana ʻana i nā papahana honua maoli.
He ala ʻoihana maikaʻi paha ka Data Analytics?
ʻAe, ʻo ka ʻikepili ʻikepili kahi koho ʻoihana akamai no ka mea ua lilo ka ʻikepili i mea koʻikoʻi o ke kaʻina hana hoʻoholo o kekahi ʻoihana. ʻO ka hopena, koi nui nā mea noiʻi ʻikepili, e hana ana iā lākou kekahi o nā koho hana kiʻekiʻe.
Pono anei ka coding i ka ʻikepili ʻikepili?
ʻAʻole lākou, e ʻoiaʻiʻo. ʻAʻole koi ʻia nā mea loiloi ʻikepili e helu ma ke ʻano he ʻāpana o kā lākou kuleana i kēlā me kēia lā. ʻAʻole pono ka hana ʻana i nā code ma nā hana ʻikepili maʻalahi, e like me ka nānā ʻana i nā ʻano ʻikepili Google Analytics.
He aha ka hana a SQL i ka ʻikepili ʻikepili?
ʻO SQL ka 'ʻiʻo a me ka ʻuala' o ka ʻikepili ʻikepili no nā poʻe he nui - hoʻohana ʻia e komo, hoʻomaʻemaʻe, a hoʻopaʻa i ka ʻikepili i loko o nā waihona. He maʻalahi ke hoʻomaopopo, akā hoʻohana ʻia ia e nā hui kiʻekiʻe o ka honua e hoʻoponopono i nā pilikia paʻakikī.
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Panina
ʻO ka ʻikepili ʻikepili ka ʻāpana akamai nui loa i ʻelua makahiki i hala, a ke hoʻomau nei.
Ua hōʻiliʻili nā ʻoihana i ka ʻikepili no nā makahiki he mau makahiki, akā ʻaʻole ʻike ka poʻe i ka hoʻohana ʻana i kēlā ʻikepili e hana i nā hoʻoholo ʻoihana ʻoi aku ka maikaʻi.
ʻO ka hopena, ke ʻimi nei nā ʻoihana i nā poʻe e hiki ke nānā a wehewehe i kēlā ʻikepili. Pono nā ʻoihana i nā poʻe hiki ke hoʻomaopopo i ka ʻikepili a unuhi i kahi ʻano hoʻomaopopo no ka hoʻokele i hiki iā lākou ke hoʻoholo i ka ʻoihana ʻoi aku ka maikaʻi. Hiki ke kapa ʻia ka poʻe me kēia mau mākau hoʻopaʻa ʻikepili he ʻikepili ʻikepili a i ʻole nā mea loiloi ʻoihana (BI).
