Ngabe Inhlangano Yakho Ilungele Ukusebenzisa Idatha Enkulu?

Idatha enkulu

Idatha enkulu ukufisa kakhulu kuneqiniso ezinhlanganweni eziningi zokumaketha. Ukuvumelana okubanzi ngenani lamasu we-Big Data kunikeza inqwaba yezinkinga zobuchwepheshe zamantongomane-nama-bolts ezidingekayo ekwakheni uhlelo lwe-ecosystem yedatha nokuletha imininingwane emisha eqhutshwa yimininingwane empilweni ngokuxhumana okwenzelwe wena.

Ungahlola ukulungela kwenhlangano ukusebenzisa i-Big Data ngokuhlaziya amandla enhlangano ezindaweni eziyisikhombisa ezibalulekile:

  1. Umbono Wamasu ukwamukelwa kweDatha Enkulu njengomnikeli obalulekile ekuhlangabezaneni nezinhloso zebhizinisi. Ukuqonda ukuzibophezela kwe-C-Suite nokuthenga kuyisinyathelo sokuqala, kulandelwa ukwabiwa kwesikhathi, ukugxila, okubekwa phambili, izinsizakusebenza namandla. Kulula ukukhuluma inkulumo. Bheka ukunqanyulwa okuvamile phakathi kwabaphathi abaphezulu abenza izinqumo zamasu kanye nososayensi bedatha yezinga lokusebenza, abahlaziyi bedatha nabathengisi be-data-centric abenza umsebenzi. Imvamisa izinqumo zithathwa ngaphandle kokufakwa okwanele kwezinga lokusebenza. Imvamisa, ukubuka okuvela phezulu nokubuka kusuka maphakathi kuhluke kakhulu.
  2. Isimo semvelo sedatha kungaba yisikhubekiso noma unike amandla. Izinkampani eziningi zibhajwe yizinhlelo zamafa nokutshalwa kwemali okushonile. Akuzona zonke izinkampani ezinombono ocacile wesikhathi esizayo ohlelwe ngamapayipi akhona. Kaningi kunokungqubuzana phakathi kwabaphathi bezobuchwepheshe bendawo ye-IT nabasebenzisi bebhizinisi abakhuphula izabelomali ezihlobene. Ezimweni eziningi, umbono ongaphambili uyiqoqo lama-workaround. Okunezela ekudidekeni yizinkampani ezingama-3500 + ezinikela ngazo zonke izindlela zezixazululo zobuchwepheshe ezenza izimangalo ezifanayo, zisebenzisa ulimi olufanayo futhi zinikeza amadili afanayo.
  3. Ukuphatha idatha isho ukuqonda imithombo yedatha, ukuba necebo lokungenisa, ukwenza okujwayelekile, ukuphepha nokubekwa phambili. Lokhu kudinga ukuhlanganiswa kwezinyathelo zokuphepha ze-agile, umbuso wezimvume ochazwe kahle nezindlela zokufinyelela nokulawulwa. Imithetho yokubusa ilinganisa ubumfihlo nokuhambisana nokusetshenziswa okuguquguqukayo nokusetshenziswa kabusha kwedatha. Imvamisa lezi zinkinga zididiyelwa noma zihlanganiswe ndawonye ngezimo kunokubonisa izinqubomgomo nezivumelwano ezidizayinwe kahle.
  4. Izibalo ezisetshenzisiwe iyinkomba yokuthi inhlangano isetshenziswe kahle kanjani analytics izinsiza futhi uyakwazi ukuletha ubuhlakani bokufakelwa nokufunda ngomshini. Imibuzo ebucayi yilena: ingabe inhlangano inokwanele yini analytics izinsiza futhi zisatshalaliswa kanjani? Ingabe analytics okugxilwe ekumaketheni nasekuqhubekeni kwamasu okusebenza, noma kuthonwe ngesikhashana? Ingabe analytics ukushayela izinqumo ezibalulekile zebhizinisi nokusebenza kahle kokuthola, ukugcina, ukunciphisa izindleko nokwethembeka?
  5. Ingqalasizinda Yezobuchwepheshe ihlola ukwakheka kwesoftware nedatha okusetshenziselwa ukufaka, ukucubungula, ukuhlanza, ukuvikela nokuvuselela imifudlana yedatha egelezela ezinkampanini eziningi. Izinkomba ezisemqoka yizinga lokuzenzakalela kanye namakhono wokumisa amasethi wedatha, ukuxazulula ubunikazi bomuntu ngamunye, ukudala izingxenye ezinengqondo nokuqhubeka nokusebenzisa idatha entsha yesikhathi sangempela. Ezinye izinkomba ezinhle ukubambisana nama-ESP, ukumaketha okuzenzakalelayo, kanye nabahlinzeki bekhompyutha yamafu.
  6. Sebenzisa Ukuthuthukiswa Kwamacala ilinganisa ikhono lenkampani yokusebenzisa empeleni idatha eyiqoqayo futhi iyicubungule. Bangakwazi yini ukubona amakhasimende “ahamba phambili”; ukubikezela ukunikezwa okuhle okulandelayo noma ukondle cishe abathembekile? Ngabe banazo izindlela zezimboni zokwenza imilayezo eyenziwe yaba ngeyakho, ukwenza ama-micro-segmentation, ukuphendula ekuziphatheni kwimidiya yeselula noma yezenhlalo noma ukudala imikhankaso eminingi yokuqukethwe ethulwa kuziteshi eziningi?
  7. Ukwamukela Amadoda Ezibalo kuyinkomba yamasiko ezinkampani; isilinganiso sesifiso sangempela senhlangano sokuhlola, ukwamukela nokuthola izindlela ezintsha nobuchwepheshe obusha. Wonke umuntu ukhipha inkulumo yokuguqulwa kwedijithali nedatha. Kepha abaningi besaba ama-WMD (izikhali zokuphazanyiswa kwezibalo). Zimbalwa izinkampani ezitshala isikhathi, izinsizakusebenza nokheshi ukwenza idatha-centricity ibe yimpahla eyisisekelo yenkampani. Ukufika ekulungiseleleni kwe-Big Data kungaba yinde, kubize futhi kukhungathekise. Ihlala idinga ushintsho olukhulu ezimweni zengqondo, ekuhambeni komsebenzi, nakubuchwepheshe. Le nkomba ilinganisa ukuzibophezela kweqiniso kwenhlangano ezinhlosweni zokusebenzisa idatha zesikhathi esizayo.

Ukubona izinzuzo zeBig Data kungukuzivocavoca ekuphathweni koshintsho. Lezi zindlela eziyisikhombisa zisenza sikwazi ukuthola umbono ocacile wokuthi inhlangano ehlinzekwayo iwela kuphi kuzinguquko. Ukuqonda lapho uqhathanisa nalapho ufuna ukuba khona kungaba wusizo uma ukuvivinya umzimba kusangulukisa.

 

UCABANGANI?

Le sayithi isebenzisa i-Akismet ukunciphisa ugaxekile. Funda ukuthi idatha yakho yokuphawula isetshenziswa kanjani.