Iyo metaverse, intelligence yekugadzira (AI), cloud computing, nharembozha, uye Internet yezvinhu (IoT) zvose zviri kuwedzera kufarirwa.
Nekuda kweizvozvo, mabhizinesi anogadzira uye anounganidza data rakawanda kupfuura nakare kose. Kana iwe uchibatanidza kune webhusaiti kana mudziyo, data inogadzirwa uye inochengetwa.
Makambani anofunga-mberi anoziva kukosha kwekushandisa data rakadaro. Zvinovabvumira, pakati pezvimwe zvinhu, kuvandudza ruzivo rwevatengi uye purofiti. Kunyangwe iwe uri kuyedza kuvandudza ruzivo rwevatengi kana kubata zvirinani hesiti yako, data inogona kubatsira kambani yako kuita zvirinani sarudzo.
Kunyanya kuita pundutso bhizinesi rako, ndiko kukurumidza kwaunokwanisa kuita kutonga kwakadaro. Iyo tsika yekushandisa chaiyo-nguva data kuita nekukurumidza bhizinesi sarudzo inozivikanwa sekushanda analytics, dzimwe nguva inozivikanwa sehungwaru hwekushanda.
Muchikamu chino, tichatarisa zvakadzama pamashandiro eanalytics maziviro, mashandisiro emakesi, uye zvimwe zvakawanda. Ngatitange.
Chii chinonzi Operational Analytics?
"Data-inotungamirwa nekuita sarudzo" inowanzotaurwa muzvikwata zvese.
Kunyangwe ichi chaimbova chinangwa chakareba, kufambira mberi mune data stack, senge matura edatha, madziva edhata, uye maturusi eBI, zvakaita kuti ruzivo rwechokwadi-nguva data rive nyore uye risingadhure kupfuura nakare kose.
Data yakawedzera kukosha nekuda kwekufambira mberi mukati machine learning, hungwaru hwekugadzira, uye kuchera data.
Nekudaro, pane chinoramba chiri dambudziko risingagadziriswe: iwo maonero anowanikwa kubva kune iyi data anobatsira chete kana akakurudzirwa kuita shanduko yebhizinesi inofambisa tsono pamberi.
Operational analytics imhando yeanalytics yebhizinesi inotarisana nekutarisa mashandiro ekambani azvino uye chaiwo-nguva. Inoshandisa chaiyo-nguva yekuongorora data uye hungwaru hwebhizinesi kuwedzera chibereko uye kugadzirisa mashandiro ezuva nezuva.
Munyika yanhasi yebhizinesi, zvakakosha kuti makambani ave nedata-chaiyo-nguva uye kujeka kwakazara mumaitiro evatengi uye maitiro ekambani kuitira kuti varidzi vagone kuchengeta mashandiro avo ezuva nezuva uye kutora matanho anodiwa ekusimudzira mutengi mufaro uye pasi. line.
Sei kushanda?
Mumakore achangopfuura, itsva yakajairwa data stack yamuka, yakatarisana nedura re data inokwanisa kutsigira zvese zvechinyakare uye zvekushandisa analytics.
Kuita ma analytics ekushanda kunowedzera kuwanikwa kune mafemu echero saizi kana iwe ukadyara mune iyi yakakosha zvivakwa. Pane zvikamu zvina kune contemporary data stack:
- Dhata Kubatanidzwa - Funga nezveFitran seETL (kubvisa, kurodha, shandura) mhinduro iyo ichabatanidza ese ako data masosi kune yako yekuchengetedza data.
- Kuchengeta Data - Funga Snowflake, nzvimbo yekuchengetera data iyo inogona kuchengetedza data yakarongeka uye isina kurongeka munzvimbo imwechete.
- Dhata Modelling: Funga nezve dbt, data modelling application iyo inokubatsira mukugadzirisa data rako nekupa raibhurari yemamodhi e data inoita kuti data rako rishandiswe kune akasiyana mashandisiro.
- Data Activation: Funga nezveTeradata, data otomatiki tekinoroji iyo inoburitsa data inogona kushandiswa kubva mudura rako redata, woiongorora otomatiki, uye woiendesa kune maturusi anoida.
Operational Analytics Shandisa Nyaya
Mazhinji akakosha bhizinesi mabasa anotsigirwa neanoshanda analytics. Uchichengeta izvi mupfungwa, heano dzimwe nzira idzo madhipatimendi akasiyana musangano rako anogona kubatsirwa nekushandisa mashandiro ekuongorora:
- Marketing: Uchishandisa data rekushandisa kupa mazano akananga ezvinhu kana kukwidziridzwa apo mutengi ari kutenga, mabhizinesi anogona kuwedzera kutengesa munguva chaiyo. Semuyenzaniso, IP kero yemutengi inogona kushandiswa kuona nzvimbo yavo uye zvine simba kuseta mitengo zvichienderana nesimba rekutenga renzvimbo.
- utariri: Kushandisa hungwaru hunoenderera mberi, mabhizinesi anogona kubata zvirinani mashandiro awo, senge kuita kudzivirira pamichina isati yaputsika kana kuzadza zvinhu zvakakurumbira zvinotengeswa.
- IT: Operational Analytics muIT inosanganisira kuunganidza uye kuongorora ruzivo rwekuita-chaiyo-nguva pamasevha ese, zvikamu zvetiweki, cloud system, uye maapplication. Ruzivo rwunobva rwashandiswa nevanyanzvi kuchengetedza nguva uye kuchengetedza mari yekushandisa.
- Supply maketani: Dzakaoma uye hadzina kusimba. Cheni dzekutengesera dziri kukanganiswa nenyaya dzakadai sekushaikwa kwezvigadzirwa uye kushomeka kwevashandi mudura, pamwe nekuvhiringwa kwekutakura zvinhu zvakaita senjodzi yemumigwagwa nemamiriro ekunze. Izvi zvinogona kukonzera maodha ekumashure pamwe nevatengi vasingagutsikane uye vadyidzani. Supply chain logistics inovandudzwa neanoshanda analytics mhinduro, iyo inopa nzwisiso huru uye inobvumira kukurumidza kuyerera kwechigadzirwa.
- Manufacturing team: Yekutarisa michina, mota, uye mitsara yekugadzira, ivo vanowanzo shandisa mashandiro ekuongorora. Ivo vanopa yakakosha kuchengetedza uye yemhando data, zvichitungamira kune hutano uye hunoshanda nzvimbo dzebasa dzine tsaona shoma uye nguva yekudzikira.
- Developers: Vanogona kutarisa kuti vatengi vari kushandisa sei zvigadzirwa zvavo munguva chaiyo uye kugadzirisa pane nhunzi vachishandisa chaiyo-nguva data. Semuyenzaniso, kana vatambi vachinetseka kupinda muchikamu chemutambo, mugadziri wemutambo wepamhepo anogona kugadzirisa dambudziko renzvimbo iyoyo kana kupa maturusi mumutambo wekubatsira vatambi kuwedzera mikana yavo yekuenderera mberi kusvika padanho rinotevera.
Operational Analytics Benefits
Pane chikonzero nei mafemu anotungamira ari kuwedzera mari yavo mukuita analytics. Rine mukana wokuva nepesvedzero yakanaka zvikuru pasangano rose. Hezvino zvikonzero zvina nei masangano anokoshesa ma analytics ekushanda asingatarise kumashure.
1. Kukurumidza kuita zvisarudzo
Kuwana nyore kuwana data mumaturusi aunoshandisa nguva dzose kunobvumira mafemu kuti ashande nekukurumidza uye nehungwaru, achipa zviyero zvakaoma kutsigira zvisarudzo zvinonetsa.
2. Kuwedzera kugutsikana kwevatengi
Kutora data uye kuishandisa kuti unzwisise zvinodiwa nemunhu kunodiwa kuti ugone kugonesa ruzivo rwevatengi.
Paunenge uchishanda nevatengi, mhinduro dzeanalytics dzinoita kuti mafemu ashande nekuwedzera nguva, kurongeka, uye tsitsi. Nekuda kweizvozvo, vatengi vane zviitiko zviri nani, vanovimbika zvakanyanya, uye vane ongororo yepamusoro.
3. Kugutsikana kwevashandi kwakagadziridzwa
Vanhu vane tarenda havadi kutambisa nguva pamabasa akaderera akadai sekupinda data, uye havadi kuronga mazuva avo nekupinda mumapuratifomu matatu akasiyana. Makambani anoenderera mberi nekushandisa mabhizinesi echinyakare ari panjodzi yekurasikirwa nevashandi vanokwanisa kune vakwikwidzi vepamusoro tekinoroji.
Makambani anotungamira anoshandisa analytics anoshanda ane workflow otomatiki kugadzirisa mabasa evashandi, zvichiita kuti zvive nyore uye nekukurumidza kuwana ruzivo, rwaunoda paunenge waruda. Uyezve, basa shoma rinoita kuti zvive nyore kuhaya uye kuchengetedza vashandi vakanaka.
4. Kuwedzera purofiti
Funga nezvemutengi ari kufona kuti aise odha yechigadzirwa chitsva kana sevhisi.
Kuve nedata pamunwe wako kunoita kuti zvikwanise kushandisa mikana painobuda.
Iwe unogona kupa vatengi zvakajairwa zvinopihwa zvavanopindura kana uine ruzivo rwakakwana, uchivabatsira kuita sarudzo dzakangwara dzekutenga nekuvandudza purofiti yakazara.
mhedziso
Mukupedzisa, nekushandisa Operational Analytics, kambani yako inoisa simba reReal-time Business Intelligence mumaoko evashandi vako vepamberi, vachivabvumira kupa kukosha kwakanyanya kukambani. Makambani ari kuwedzera kutendeukira kune chaiyo-nguva yekugadzirisa data semitengo yemakore-yakavakirwa zviwanikwa (sevhavha uye matura data) inodonha.
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