Ukuhweba nge-inthanethi kuthandwa kakhulu kangangokuthi kuholele ekuthuthukisweni kobuchwepheshe obusha njenge-BIG DATA obenza kube lula ukucubungula ulwazi oluningi.
Izizathu ezenza amakhasimende athenge ku-inthanethi zilula kakhulu; 91% wabathengi abaku-inthanethi bacabanga ukuthi izindleko zokulethwa ezisebenzayo neziqondile ziyisihluthulelo sokuthenga oku-inthanethi okwanelisayo.
Ngakolunye uhlangothi, sinenqubo yokubuyisela izinto , eyinkimbinkimbi kumawebhusayithi amaningi futhi ehilela inqubo ende kakhulu futhi eyisicefe, kanti kwezentengiselwano ezivamile ungabuyisela izinto ngokushesha.
Umkhakha wezohwebo nge-inthanethi ushintsha njalo. Ukwenziwa kwedijithali kwezimakethe zomhlaba wonke kuqhubeka ngokushesha, futhi kuzo zonke izinhlaka zezohwebo, ukwanda okusheshayo kokuthengiswa kwe-inthanethi uma kuqhathaniswa nokuthengisa okuvamile kungabonakala.
Ukulibala kwezinye izinkampani kuyabonakala; noma ubani ongenalo ipulatifomu yakhe eku-inthanethi uphuthelwa izinkulungwane zokuthengisa ngosuku, ngoba nge-inthanethi, ukufinyelela izinto ezithengiswayo kusuka noma kuphi emhlabeni kuyinto eqinisekile.
Uyini umkhuba wamanje ku-e-Commerce?
Ukuhweba nge-inthanethi eSpain kumelela u-11% wemali ethengiwe , kanti imfashini iyaqhubeka nokuba yimboni ebhalisa imali eningi kakhulu futhi imelela u-48% wemali ethengiwe ku-inthanethi.
Ukukhula kwe-e-commerce akunakuvinjelwa, kwephula amarekhodi okuthengisa minyaka yonke ngezikhathi ezifana ne-Black Friday, i-Cyber ​​​​Monday, ukuthenga kukaKhisimusi, kanye nokuthengiswa okulindelwe kakhulu ngoJanuwari nangoFebhuwari. Lezi zikhathi ngokungangabazeki ziyisikhathi esiphezulu sokuhweba online futhi ziletha inselelo enkulu emkhakheni wezokuthutha kanye nezokuthutha ezweni lethu.
Umkhuba kwezentengiselwano ze-e ungabonakala kuhlelo lwesibili lwe- 'eShopper Barometer ', inhlolovo enemininingwane eyenziwe yi-DPDgroup ukuqonda izidingo, izici, kanye nezisusa eziyinhloko zabathengi be-inthanethi. Imiphumela yalo mbiko inikeza umbono obanzi ngemikhuba yokuthenga yamanje kwezentengiselwano ze-e.
Ngakho-ke yini esiyaziyo ngabathengi?
Lokho kukhona tres izinhlobo ezahlukahlukene zabathengi be-inthanethi ezweni lethu:
- Abathengi abakhulu.
- Isilinganiso sabathengi, abathola isilinganiso samaphakeji angu-2,7 ngenyanga futhi abamele u-11% wokuthengiswa okuphelele ngonyaka ku-inthanethi.
- Abathengi abancane, ngamaphakeji angu-1,3 noma ngaphansi okutholwe ngenyanga, amele u-2% wenani lonyaka elisetshenziswe ku-ECommerce.
Ngubani othenga okuningi?
Uma sibheka okungenhla mayelana neqiniso lokuthi i-eCommerce isivele imele u-11% wenani elithengiwe eSpain, imfashini iyaqhubeka nokuba yimboni ebhalisa imisebenzi eminingi futhi imele u-48% wokuthengwa kwe-inthanethi okwenziwe eSpain.
Iningi lokuthenga lenziwa ngabantu abaneminyaka engaphezu kwengu-57, kanti abangaphezu kuka- 57% bavuma ukuthi bathenga lolu hlobo lwemikhiqizo ku-inthanethi.
Izikhundla ezilandelayo ezingeni lokuthengisa ziphethwe yimikhakha yobuhle nobuchwepheshe, ebalelwa ku-38% kanye no-36% ngokulandelana kokuthengwa kwe -inthanethi eSpain . Umbiko uqokomisa ukuvela kokuthengwa kokudla neziphuzo ezintsha ku-inthanethi phakathi kweyishumi eziphezulu, okumelela u-18% wokuthengiswa kwe-inthanethi eSpain. Ngaphezu kwalokho, u-14% wabantu baseSpain abathenga ku-inthanethi bayavuma ukuthi bathenga ukudla ku-inthanethi okungenani kanye ngenyanga.
Ukuqonda imibono yabathengi abaku-inthanethi kuyisihluthulelo sempumelelo kwezentengiselwano ze-e. Sonke siyavuma ukuthi ukuthenga okulula nokuphephile kuzothinta kahle ukukhula kwamabhizinisi aku-inthanethi, njengoba amakhasimende anelisekile azophinda lokho okuhlangenwe nakho futhi akuncome kubangani babo nomndeni. Lolu cwaningo olufanayo lubonisa lokhu, lubonisa ukuthi ama-85% abathengi bathole ukuthenga kwabo ku-inthanethi kulula, kanti ama-75% aneliseke kakhulu yilokho okuhlangenwe nakho.
Yini i-Big Data?
Ngamafuphi, i-Big Data iwukuphathwa nokuhlaziywa kolwazi oluningi noma idatha engenakucutshungulwa ngendlela evamile uhlelo oluvamile lokusebenza, njengoba idlula amakhono esofthiwe evamile futhi idlula imikhawulo yokucubungula i-algorithmic.
Lo mqondo uhlanganisa intuthuko yezobuchwepheshe emikhakheni ehlukahlukene, njengengqalasizinda , ubuchwepheshe, kanye nezinsizakalo , eziklanyelwe ngqo ukubhekana nokucutshungulwa kwedatha eningi ehlelekile, engahlelekile, noma engahlelekile ngokuphelele. Le datha ihlanganisa imiyalezo yezokuxhumana, amafayela alalelwayo, izithombe zedijithali, idatha yamafomu, ama-imeyili, amasignali eselula, idatha yezinzwa, kanye nedatha yocwaningo. Le mithombo yedatha ingafaka izinzwa ezahlukahlukene, amakhamera, izikena zezokwelapha, kanye nezinhlelo zezithombe.
Inhloso eyinhloko yezinhlelo ze-Big Data , njengakwezinhlelo ezijwayelekile, ukuguqula idatha eyinkimbinkimbi ibe ulwazi olufinyelelekayo nolubonakalayo olusiza ekwenzeni izinqumo ngesikhathi sangempela.
Izinkampani namuhla sezivele zisebenzisa i-Big Data ukuqonda iphrofayili, izidingo, kanye nezici zamakhasimende azo kanye ne-human capital maqondana nemikhiqizo noma izinsizakalo abazithengisayo. Lokhu kushintshe indlela ikhasimende elibhekwa ngayo njengelibalulekile, okuvumela izinkampani ukuthi zivumelanise ukuxhumana kwazo namakhasimende kanye nezinsizakalo ezizinikezayo.
Ukuhlanganisa umqondo we-Big Data nenani elikhulu ledatha akuyona into entsha. Iningi lezinkampani ezinkulu sekuyisikhathi eside zisingatha inani elikhulu lolwazi, kodwa zaphoqeleka ukusebenzisa obunye ubuchwepheshe njengezindawo zokugcina idatha namathuluzi okuhlaziya anamandla ukuze zicubungule kahle la manani amakhulu, ngaphambi kokufika kwesofthiwe ye-Hadoop. Intuthuko yezobuchwepheshe iholele ekwandeni okukhulu kwenani lolwazi oluphathwa yilezi zinhlelo zokusebenza.
Izinsika ezi-5 ze Idatha enkulu
Ama-'V' amathathu e-Big Data yizimpawu eziyinhloko ezisetshenziswa ukuyibona: Umthamo , Ukuhlukahluka , kanye neVelocity . Kodwa ngolwazi olutholwe yizinkampani eziholayo kulo mkhakha wokuphatha inani elikhulu lolwazi, incazelo yokuqala iye yandiswa, kwengezwa izici ezintsha ezicacile njengeVeracity kanye neValue of the data.
Ibizwa nge-Big Data lapho amavolumu edlula amandla nemikhawulo yesoftware ejwayelekile, kungaba yiWindows, iMac noma neLinux, ezocutshungulwa ngaphandle kwezinkinga.
Umqondo wevolumu ushintsha njalo ngenxa yentuthuko yezobuchwepheshe esheshayo, evumela ukucutshungulwa kwenani elikhulu lolwazi. Ukuze kucaciswe leli gama, inani elikhulu lolwazi ngamakhulu noma izinkulungwane zama-terabyte noma ama-petabyte , amanani amakhulu kakhulu kunezinkulungwane zama-gigabyte ezivamile ikhompyutha ejwayele ukuzicubungula. Lo mqondo wevolumu nawo uyahlukahluka kakhulu, njengoba sicabanga kakhulu ngenani ledatha elicutshungulwayo.
Ulwazi olungacutshungulwa yi - Data Warehouses luwulwazi oluhlelekile oludlule ezihlungini eziningi zokulawula ikhwalithi enhle kakhulu, ukuze kuqinisekiswe ukuthi ulwazi olucutshungulwayo lunokunemba nokunemba okunqunyiwe.
Uma sikhuluma nge-Big Data, sikhuluma ngolwazi olungahlelwa kancane noma olungahlelwanga ngokuphelele . Ukucubungula lolu lwazi olungahlelwanga kudinga ubuchwepheshe obuhlukile futhi kuvumela abasebenzisi ukuthi benze izinqumo ngokusekelwe olwazini olungacacile. Iningi lala ma-algorithms lihlobene nezinhlelo ze-logic ezithuthukisiwe, ezingakathuthukiswa ngokugcwele.
Ukukhuluma ngomqondo we okuhlukahlukene, kubhekiswa ezinhlotsheni zedatha etholwa uhlelo, lezi zingu-3:
- Kuhleliwe
- Ukwakheka okuyingxenye
- Akuhlelekile
Okokugcina, umqondo wejubane ngokusobala ubhekisela ekusheshiseni lapho kwamukelwa khona, kucutshungulwe, futhi kudluliselwe khona imiqulu emikhulu yedatha ukuze kunikezwe ulwazi ngokwenza izinqumo. Izinhlelo eziningi zokusebenza ezivamile azikwazi ukuhlaziya ngokushesha inani elikhulu kangaka lolwazi, kodwa ukufaka umqondo wokucubungula idatha ngesikhathi sangempela kubalulekile ezinhlelweni zokuthola ukukhwabanisa noma ezinikezweni ezenziwe ngokwezifiso ezithuthukisiwe ezinikezwa amakhasimende njengamanje, kucatshangelwa ukuthanda kwazo nezinye izici ezinquma ukuthi yini engabathakazelisa.
Ukuphetha, ubuqotho buwukuthembeka kolwazi olucutshunguliwe , ukukhipha idatha esezingeni eliphezulu, ukuthuthukisa ukubonakala okungokwemvelo kwabanye, njengesikhathi, umnotho phakathi kokunye, okuzosiza ekwenzeni izinqumo ezingcono.
Okokugcina, ukubaluleka nokubaluleka kolwazi oluyisisekelo lwebhizinisi kuyagcizelelwa . Ukwazi ukuthi yiluphi ulwazi okufanele luhlaziywe kwenza yonke inqubo ibe lula ngokuyikhetha kusengaphambili kubalulekile ukuze kube nesivinini nokunemba. Eqinisweni, kakade sekuyinkampani yesibili efunwa kakhulu eSpain.