Ngokuvumelana ne
Ukubuyekezwa kwe-Gartner Peer Insights kanye nezilinganiso, I-Microsoft (Power BI), i-Tableau, ne-Qlik ivamise ukuba ngabaholi bemboni ku-analytics kanye nezinkundla zezobunhloli bebhizinisi. Nokho, lezi zinkundla eziphezulu ziwuthuthukisa kanjani umkhakha wokuhlaziya idatha, yini ehlukanisayo
kubo, futhi yiziphi ezinye izindlela zabo? 

Zethule emhlabeni wokuxoxa izindaba ngedatha. Le ndlela enamandla yenza amabhizinisi, ikakhulukazi lawo asembonini yamabhange, akwazi ukuxhumana kahle nangendlela enembile imininingwane etholakala kudatha yawo. Kuvele inkathi entsha yokwethulwa kwedatha
sibonga amathuluzi okubona ngeso lengqondo afana ne-Power BI, enika amandla ukulandisa okunamandla okuthonya isu nokwenza izinqumo. Kulesi sihloko. ake sihlole ama-nuances wokuxoxwa kwezindaba zedatha kanye nokusebenza kwayo okubalulekile embonini yamabhange, njengoba kubonisiwe
ngocwaningo lwe-Power BI olubandakanyayo. 

Kuyini Ukuxoxa Ngedatha?

Ukuxoxwa kwezindaba zedatha kuyindlela yokudlulisa umlayezo ohlanganisa ukubonwa kwedatha nezindlela zokulandisa ukuze kwenziwe izindaba zedatha eziyinkimbinkimbi eziheha futhi ezibandakanya abantu. Izithameli zingaqonda ingqikithi yokubonga kwedatha kulokhu kuhlanganiswa, okuyinto
kwenza kuqondeke futhi kuhlobane. Ngokuyisisekelo, ukuxoxwa kwezindaba zedatha kuhloswe ngakho ukuvala igebe elikhona phakathi kwezinto ezibonakalayo nezingabonakali, kanye naphakathi kwesizinda somthamo kanye nekhwalithi. Ake sikuhlole lokhu ngokuningiliziwe.

Iqhaza Lokubonwa Kwedatha

Ukubona idatha, okubandakanya ukuguqula amasethi edatha abe amafomethi abonakalayo njengamashadi, amagrafu, amamephu, ne-infographics, kuyisisekelo sokuxoxwa kwezindaba zedatha. Lezi zakhi ezibukwayo zibalulekile ekulandiseni izindaba zedatha ngoba zenza ulwazi oluyinkimbinkimbi lube lula
qonda. Ukubukwa kwedatha kuveza amaphethini afihliwe, izitayela, nobudlelwano kudatha, kubeka isisekelo sokulandisa.

Ukuhlola vs. Ukubonwa Okuchazayo

Ukubukwa kwedatha kuhlukaniswe izinhlobo ezimbili: okuhlolayo kanye nencazelo. Lokhu kuhlukaniswa kubalulekile ekunqumeni indlela yokuxoxa izindaba zedatha:

• Ukubonwa Kokuhlola kusho indlela esetshenziswa phakathi nesigaba sophenyo sokuhlaziya idatha. Uma ukulandisa kungakatholakali, okubonwayo okuhlola kungasiza ukuveza indaba efihliwe ngaphakathi kwedatha. Imibuzo enjengokuthi “Kwenzenjani
  Imali engenayo yokuthengisa iyashintsha ngokuhamba kwesikhathi?" noma “Kungani imali engenayo yokuthengisa yenyuka ngesizini ethile?” zidingidwa ngale nqubo yokuhlola, ibeka inkundla yokuthi indaba yembuleke.

• Ukubona ngeso lengqondo okuchazayo kusetshenziswa lapho indaba isiqediwe futhi umgomo uwukukhulumisana nemibono ethile nezethameli. Okubonwayo kuklanyelwe ukudlulisa izici ezithile zendaba noma yonke indaba, kuqinisekiswe ukuthi izethameli ziyaqonda.
  umlayezo ohloswe ngumxoxi wedatha.

Bona umdwebo ukuze uqonde ukuhlangana kwalokhu okubili nokuxoxwa kwezindaba zedatha:

Isakhiwo Sokulandisa Okukhethekile

Ukuxoxwa kwezindaba zedatha okuphumelelayo kunesakhiwo sokulandisa esihlanganisa isiqalo esicacile (isingeniso senkinga noma umongo), maphakathi (ukuhlaziywa kwedatha nemininingwane), nesiphetho (izincomo). 

Ukuqaqa Izingxenye Zokuxoxa Indaba Yedatha

• Ukuhlonza izethameli: Ukwenza ngokwezifiso ukulandisa nokubonwayo ukuze kubonise isizinda sezilaleli nezithakazelo.

• Ukuchaza Indaba: Ukudala ukulandisa okuhambisanayo nokufushane okubhekana nenkinga ethile yebhizinisi noma umgomo.

• Ukukhetha Ukubuka Okulungile: Ukukhetha izinhlobo ezifanele zamashadi, amagrafu, nokubonwayo ukuze kugqanyiswe imininingwane ebalulekile namathrendi.

• Ukwengeza Umongo: Ukunikeza umongo nezincazelo ukusiza izethameli ziqonde ukubaluleka kwedatha.

• Ukudala Ukuxhumana Kwemizwa: Kuhlanganisa izici zokuxoxa ezivusa imizwa, okwenza idatha ihlobane kakhulu futhi ikhumbuleke.

I-Power BI Case Study Emkhakheni Wamabhange

Ake sicabangele isibonelo esithile sendlela Ukuxoxa Indaba Yedatha okusebenza ngayo endaweni yamabhange.

Ukugcinwa kwamakhasimende kulo mkhakha kubaluleke ngokulinganayo njengokutholwa kwamakhasimende. Ibhange elikhulu lalisesimweni lapho izinga lokushintshashintsha lalikhuphuka, lisabisa ngokuthatha isikhundla salo semakethe kanye nemali engenayo. Ukuhlangabezana nale nselelo, i-Power BI ingene, yona
iyithuluzi elisebenzisanayo elinikeza ukuhlaziya idatha ephezulu kanye nokusebenza kokubona ngeso lengqondo. Lolu cwaningo oluyisibonelo lugqamisa ukusetshenziswa kwamasu kwe-Power BI yibhange ukuthuthukisa ukugcinwa kwamakhasimende ngokukhomba amaphethini kudatha yokuhweba enamandla
amandla okubikezela mayelana nokuqubuka okungenzeka.

Isitatimende Sezinkinga

Ngakho-ke, cabanga ukuthi ibhange libone iphethini elikhathazayo: ngokuhamba kwesikhathi, inani lamakhasimende asuka ngenxa yezimbangi lalikhuphuka. I-churn rate ayikhombisanga nje kuphela ukuthi ibe nomthelela omubi kangakanani enzuzweni yebhange kodwa iphinde yagqamisa amaphutha okungenzeka
ukwaneliseka kwamakhasimende kanye nokuzibandakanya. Ubunzima bekuwukuhlela imiqulu emikhulu yedatha yokuthengiselana kanye nezibalo zabantu bamakhasimende nokuziphatha ukuze kutholwe izimbangela zokuqubuka. Ngakho-ke, inhloso yesu eliqhutshwa idatha akufanele nje kuphela
begciniwe kodwa ukweneliseka kwenyuke sekukonke.

Ukuhlaziya Data

Khona manjalo, ibhange laqala uhambo lokunqamula umhlaba wezibalo ezithuthukile nge-Power BI. Okokuqala, sihlanganise idatha yokwenziwayo, izibalo zabantu bamakhasimende, namaphethini okuziphatha ukuze sakhe idathasethi eyodwa. Izici zezibalo ezithuthukisiwe
etholakala ku-Power BI ibenze bakwazi ukuhlola ngokujulile le dathasethi futhi bakhiphe amathrendi namaphethini abalulekile. Phakathi kwabo, bangakwazi ukulandelela izingxenye zamakhasimende okungenzeka ukuthi zihambe, izinhlobo zemisebenzi ekhombisa isiphithiphithi esizayo, kanye
njengezikhathi ezinomsebenzi we-churn owengeziwe.

Okubona

Ngemva kokuhlaziya idatha, isinyathelo esilandelayo ukwenza leyo mininingwane isebenziseke. Amadeshibhodi asebenzisanayo e-Power BI ayasebenza, ahlinzeka ngokubonwa kwedatha okucacile, okushukumisayo. Lawa madeshibhodi agqamisa amasegimenti wamakhasimende asengozini enkulu yokuphazamiseka nokudalula
izici ezinomthelela esinqumweni sekhasimende sokuhamba. Ibhange lenza idatha ihehe futhi lenze le mininingwane isakazwe kuyo yonke iminyango ukuze kuqinisekiswe ukuthi abathatha izinqumo banolwazi oludingekayo ukuze bathathe izinyathelo ezinqala.

Okulandelanayo

Noma kunjalo, idatha iyodwa, kungakhathaliseki ukuthi ihlaziywe ngokunembe kangakanani, ayikwazi ukukhuthaza isenzo ngaphandle kokulandisa okuphoqelelayo. Ibhange lenze indaba mayelana nedatha, ligcizelela ukubaluleka okubalulekile kokugcinwa kwamakhasimende, umthelela obonakalayo wokungqubuzana kwebhange.
imali engenayo, kanye namasu akhonjiwe okubhekana nalokhu kuqubuka. Lokhu kulandisa kusebenze ukwazisa nokugqugquzela yonke inhlangano ekufezeni umgomo obumbene.

wesifundo

Ukusebenzisa imininingwane etholwe ku-Power BI ngobuchule kuguqule indlela yebhange ekuzibandakanyeni namakhasimende. Ngokuhlaziya okuningiliziwe nokubonwa okucacile, ibhange lethule imikhankaso yokumaketha eqondiwe kanye neminikelo yomuntu siqu esekelwe ezidingweni nasekuziphatheni.
yezigaba zamakhasimende ezinobungozi obukhulu. Ngenxa yalokho, amanani entengo yamakhasimende ehla kakhulu, kuyilapho ukwaneliseka kwamakhasimende nokwethembeka kukhuphuka.

Kulolu hlelo, ibhange labhekana nenselelo enzima yokunciphisa ukuxova kwamakhasimende futhi laphinde laqinisekisa ukuzibophezela kwalo ekusebenziseni ubuchwepheshe ukuze kuzuze amaqhinga. Lolu cwaningo lwesibonelo lubonisa ukuthi i-Power BI ingaba kanjani ithuluzi elinamandla lokuqonda nokwanda
ukwethembeka kwamakhasimende, ekugcineni kuzuze impumelelo yesikhathi eside embonini yamabhange enokuncintisana kakhulu.

Imibono Eyinhloko

Indaba yethu ibheka izikhungo zebhange elikhulu elasebenzisa i-Power BI ukuze libhekane nezingcaphuno ezikhulayo zokuxoxisana kwamakhasimende, okuhloswe ngazo ukuthuthukisa amasu okugcina amakhasimende kanye nenjabulo. Ibhange lazibekela izinhloso ezinkulu zokuqalisa ukusebenza kwe-Power BI:

Isivinini Sokukhishwa Kwedatha: Ihlose ukuthola isaphulelo esingu-50% ngesikhathi sokukhipha, kusukela kumaminithi angu-60 kuya kumaminithi angu-30, kuthuthukisa ukusebenza.

Ukusebenza Kwenqubo Ye-ETL: Ukuzuza inani lokugcwaliseka elingu-96% lemisebenzi ye-ETL, ngenani eliphansi lama-30% ngesikhathi sokuguqulwa kolwazi, okuqinisekisa ukwethembeka kanye nesivinini.

Ukuthuthukiswa Kwemodeli Yedatha: Ukusetha isikhathi sokuvuselela samaminithi angu-15 samamodeli ezibalo kanye nesikhathi sokusabela kombuzo esingaphansi kwamasekhondi angu-3, ​​kuthuthukisa ukusebenza.

Bika Isivinini Sokunikezwa: Iqondisa isikhathi sokulayisha idokhumenti esingaphansi kwamasekhondi angu-6 kanye nokunikezwa okubonakalayo okungaphansi kwamasekhondi angu-2, kuthuthukisa i-UX.

I-Data Compression Ratio: Ihloselwe okungenani isilinganiso esingu-10:1 sokuminyanisa ulwazi, ukukhulisa ukusetshenziswa kwesitoreji nokwehlisa izindleko.

Ukuthobela Ukuphathwa Kwedatha: Ukugcina amaphuzu amadokhumenti omugqa wedatha okungenani angu-92% kanye nesilinganiso sokuphumelela kokuphathwa kokufinyelela kwedatha sama-98%, okuqinisekisa ukuvikelwa nokuhambisana.

Isiphetho

Elinye lamathuluzi asebenza kahle kakhulu ukuze amabhizinisi axhumane nemininingwane futhi ashayele isenzo ukuxoxa izindaba zedatha. Kunamapulatifomu amaningi okubuka njenge-Power BI, ne-Tableau, phakathi kokunye, anamakhono okubuka anamandla avumela ukuthi
abasebenzisi ukudala ukulandisa okuphoqayo. Ngakho-ke, ubuciko bokuxoxa izindaba zedatha, obuhambisana nezindlela zokwethulwa kokubukwayo ezinethonya, kuyisici esibalulekile kunoma iyiphi inhlangano ehlose ukuvula inani layo langempela ledatha.

• I-SEO Powered Content & PR Distribution. Khuliswa Namuhla.
• I-PlatoData.Network Vertical Generative Ai. Zinike Amandla. Finyelela Lapha.
• I-PlatoAiStream. I-Web3 Intelligence. Ulwazi Lukhulisiwe. Finyelela Lapha.
• I-PlatoESG. Ikhabhoni, I-CleanTech, Amandla, Environment, Ilanga, Ukuphathwa Kwemfucuza. Finyelela Lapha.
• I-PlatoHealth. I-Biotech kanye ne-Clinical Trials Intelligence. Finyelela Lapha.
• Source: https://www.finextra.com/blogposting/25967/data-storytelling-with-visualization-tools?utm_medium=rssfinextra&utm_source=finextrablogs