Zviri Mukati[Viga][Ratidza]
- 1. Unotsanangura sei njere dzebhizinesi?
- 2. Chii chinosiyanisa muongorori webhizimisi kubva kune data analyst?
- 3. Ndeapi maturusi eBusiness Intelligence (BI) anonyanya kushandiswa anoshandiswa neBusiness Analysts?
- 4. Ko bhizimusi analytics universe inosanganisirei?
- 5. Ndeapi mazano ehunyanzvi auchashandisa kuita BI system?
- 6. Chii chaizvo chinonzi feasibility study?
- 7. Rondedzera kuchengetwa kwedata.
- 8. Chii chaizvo chinonzi OLAP?
- 9. INVEST – Chii?
- 10. Online Transaction Processing (OLTP) - chii ichocho?
- 11. Matafura eChokwadi uye Dimension: chii?
- 12. Ndeapi mamwe maitiro eData Warehouse?
- 13. Chii chinangwa che data normalization?
- 14. Chii chaizvo chinonzi akaunganidzwa?
- 15. Ndeapi marudzi akasiyana eSQL JOIN mabasa aripo?
- 16. Rondedzera tafura yepivot.
- 17. Unoziva here nezvedzimwe nzira dzakaita seMoSCoW neSWOT?
- 18. Ndeapi mabasa eUML?
- 19. Tsanangura ERP muhuchenjeri hwebhizimisi.
- 20. Panyaya yehungwaru hwebhizinesi, ungatsanangura sei SCM?
- 21. Unogona here kutsanangura SRS nezvikamu zvayo zvikuru?
- 22. Rondedzera BRD. Chii chinoisiyanisa kubva kune SRS?
- 23. Tsanangura pfungwa ye e-commerce maererano nehungwaru hwebhizinesi.
- 24. Chii chaizvo chinonzi RUP methodology?
- 25. Chii chaizvo chinonzi RAD methodology?
- 26. Unorevei chaizvoizvo nechinodikanwa? Unogona here kusiyanisa zvinodiwa nezvinodiwa?
- 27. Rondedzera kuchera data.
- 28. Ungarondedzera sei chinodikanwa sechinokwana kana kuti chakanaka?
- 29. Chii chaizvo chinonzi executive information system (EIS)?
- 30. Chii chinonzi kunyangira, uye kunogona kudziviswa sei?
- 31. Dimensional Modelling (DM) - chii ichocho?
- 32. Chii chaizvoizvo chinodiwa kuisa pokutanga?
- 33. Iwe unotenda kuti kuedza kunofanira kusanganisira muongorori webhizimisi?
- 34. Ndedzipi mhando dzakawanda dzehutungamiriri?
- 35. Tsanangura ongororo yePareto.
- 36. Rondedzera ongororo yaKano.
- 37. The Agile Manifesto: Chii?
- 38. Gap analysis: Chii?
- mhedziso
Hungwaru hwebhizinesi chingori mutsara wechishandiso chinobatsira mushandisi kuita sarudzo dzemabatiro ebhizinesi kana zvakakosha zvine chekuita nebhizinesi.
Kutungamirirwa kweimwe sangano rekuwedzera kwebhizimisi remushandisi kunoitwa nyore.
Nerubatsiro rwemishumo yakakodzera uye data yechero sangano, BI inobatsira mushandisi mukuita sarudzo inoguma nekukura mukambani yavo, izvo zvakakosha.
Saka iwe unoda kushanda muhungwaru hwebhizinesi uye uve nechishuwo kana chinangwa chekudaro, asi hauzive kuti ungapasa sei bvunzurudzo yehungwaru hwebhizinesi kana kuti ingangove mibvunzo ipi.
Kubvunzurudza kwese kwakasiyana, uye basa rega rega rine rakasiyana seti yezvinodiwa. Kuti tikubatsire kuti ubudirire mubvunzurudzo yako, takagadzira rondedzero yemibvunzo inowanzo bvunzwa uye nemhinduro dzayo.
Iwe unogona nekukurumidza uye nekungopindura iyi mibvunzo yehungwaru yekubvunzurudza bhizinesi.
1. Unotsanangura sei njere dzebhizinesi?
Hungwaru hwebhizinesi hunogona kutsanangurwa semubatanidzwa weData Analytics uye maitiro ekuunganidza, kuchengetedza, uye kutonga.
Inotsvaga kuongorora nekushandura dhata neruzivo kuita zvinobatika uye zvinobatsira ruzivo.
Aya maonero ane simba rakanaka pamhando dzakawanda dzesangano dzesarudzo dzebhizinesi. Mumashoko akareruka, tsananguro yeBusiness Intelligence yaizoreva amburera iyo inosanganisira maturusi edatha, kuona data, kucherwa kwedata, zvivakwa, data analytics, zvichingodaro, kuitira kupa zvipfupiso zviri nyore uye zvinonzwisisika zvinogona kubatsira masangano mukugadzira data- zvisarudzo zvinotungamirirwa.
2. Chii chinosiyanisa muongorori webhizimisi kubva kune data analyst?
Dhata Muongorori:
- Zvimwe zvekugadzirisa matambudziko uye hunyanzvi hwekuongorora data hunodiwa pachinzvimbo.
- Musangano, inotamba basa rakakura rekushanda.
- Kuchera data, SQL, nhamba, uye humwe hunyanzvi hunodiwa.
Bhizinesi Muongorori:
- Kuona data uye kugona kuita sarudzo kunofanirwa kuvandudzwa.
- Musangano, rinoshanda basa rakawanda.
- Kune iyi chinzvimbo, iwe unofanirwa kuve neruzivo mune bhizinesi njere, data warehousing, analytics, nezvimwe.
3. Ndeapi maturusi eBusiness Intelligence (BI) anonyanya kushandiswa anoshandiswa neBusiness Analysts?
- Tableau
- SAS
- Pentaho
- Business Zvinhu
- OBIEE
- Vadivelu Comedy QlikView
- Hyperion
- BI yeMicrosoft
- Cognos
- Dundas BI
- Google Analytics
- MicroStrokisi
4. Ko bhizimusi analytics universe inosanganisirei?
Pakati pedatabase uye mushandisi interface, pane chimiro che semantic layer inonzi universe. Icho chaicho chimwe chezviratidziro zvinobatanidza mutengi (mushandisi webhizinesi) nedura re data.
Inotsanangura hukama hwese pakati pematafura akasiyana mudura re data.
5. Ndeapi mazano ehunyanzvi auchashandisa kuita BI system?
Bvisa data raw kubva mudura rekambani. Panogona kunge paine akati wandei heterogeneous dhatabhesi uko iyo data inowanikwa.
Iyo data inobva yacheneswa kuitira kuti iiswe mudura re data nekubatanidza tafura uye kugadzira data cubes.
Chinhu chekupedzisira chinogona kuitwa nevanoongorora bhizinesi kubvisa ruzivo rwebhizinesi kubva kune akachena dhataseti uchishandisa BI masisitimu, kukumbira ad-hoc mishumo, ongorora iwo, uye fungidziro yebhizinesi sarudzo.
6. Chii chaizvo chinonzi feasibility study?
A BA inofanirwa kudzidza uye kunzwisisa zvinodikanwa uye nyaya dzebhizinesi kana chirongwa isati yatanga chiyero chedambudziko.
Dambudziko rebhizimisi rinokurudzirwa kuti rivepo (mukana wekubudirira) rinotariswa kuburikidza neruzivo rwezvinogoneka. Inotsigira kutarisa kweprojekiti uye ruzivo rutsva rwemukana.
7. Rondedzera kuchengetwa kwedata.
Kuchengetedzwa kwedata kunogona kutariswa sehurongwa hunoshandiswa senzvimbo yekuchengetedza, kuronga, uye kushuma data kubva kune akati wandei akasiyana masosi.
Iyi data inogona kuwanikwa muSQL Server, Excel sheets, Oracle dhatabhesi, kana Postgres dhatabhesi. Vaongorori vebhizinesi vanogona kuwana ese apfuura mishumo ine chekuita neiyo data nekushandisa iyo repository nzira, iyo iyo Data Warehouse inoshandisa.
8. Chii chaizvo chinonzi OLAP?
Online Analytical Processing, kana OLAP, ishoko rehunyanzvi rinoshandiswa kutsanangura tekinoroji inoshandiswa mumaturusi mazhinji eBI uye maapplication. Izvi zvinogonesa kupedzwa kweakaoma analytical computations.
Pamusoro pezvo, inoongorora mafambiro, inopedzisa computations yakaoma (pfupiso, kuverenga, avhareji, min, max), uye inoshandisa advanced data modeling muBI system. Pamusoro pezvo, chinangwa chekutanga kukurumidza kuverengera mishumo uye kuderedza nguva inotora kuti mibvunzo ipindurwe.
9. INVEST – Chii?
Yakazvimirira, Inokurukurirana, Inokosheswa, Inoyerwa, Yakakura Zvakafanira, uye Inoedzwa inonzi INVEST. Mamaneja epurojekiti nevaongorori vebhizinesi vese vanoshandisa mutsara uyu kureva kuendesa zvemhando yepamusoro masevhisi uye zvinhu.
10. Online Transaction Processing (OLTP) - chii ichocho?
Iwe unogona kufunga nezve OLTP masisitimu semuunganidzwa wakakura wekuisa, kubvisa, uye kugadzirisa diki data transaction. Aya dhatabhesi anoshanda uye anogona kubata mubvunzo nekukurumidza.
Kuenderana uye kutendeseka kwe data zvakare kuri pasi pekutonga kwayo. Inoshandawo senzira yekuona kuti inoshanda sei iyo OLTP sisitimu nenhamba yekutengeserana kwainoita sekondi yega yega.
11. Matafura eChokwadi uye Dimension: chii?
Tafura yechokwadi mukuchengetedza data inoumbwa nenhamba dzetsika uye dimension makiyi ebhizinesi maitiro. Quantitative data inoshandiswa pakuongorora inoratidzwa mutafura yechokwadi.
Kusiyana nematafura echokwadi, ari matafura ehuwandu hweduramazwi, matafura ezviyero anosanganisira ruzivo rwenzira dzakasiyana-siyana dzinogona kuongororwa ruzivo rwuri mutafura.
12. Ndeapi mamwe maitiro eData Warehouse?
- Vagadziri-vanoita sarudzo vanoshandisa yakagadziriswa uye yakaongororwa data kubva mudura re data kuita zvine hungwaru uye zvine hungwaru kutonga.
- Iro dhatabhesi rakasiyana rinochengetwa rakasiyana kubva kune dhatabhesi rekushandisa uye rinopihwa basa rekuchengetedza marekodhi eruzivo.
- Vaongorori vekambani vanogona kuona maitiro ebhizinesi azvino nekuongorora data rakachengetwa mudura.
- Pamusoro pezvo, inotarisira kuunganidza nhoroondo yekuongorora data.
13. Chii chinangwa che data normalization?
Data normalization ndiyo dhizaini yekuronga nekugadzirisa data zvekuti marekodhi ese neminda zvine chitarisiko chakafanana. Data normalization ine zvakawanda zvakanakira.
Maitirwo acho, semuenzaniso, anobatsira mukuchengetedza kutendeseka uye kubviswa kweiyo duplicate data. Pamusoro pezvo, nekuti ivo vatoziva nzira iyo bhizinesi rinoronga data raro, vanoongorora vanogona kukurumidza kutarisa kune akasiyana dhata.
14. Chii chaizvo chinonzi akaunganidzwa?
Izvo zvinokwanisika kufunga nezve akaunganidzwa semhando yedata inogona kuwanikwa muaggregate table. Akasiyana aggregate mabasa anoiswa pakuverenga kweaya akaunganidzwa.
Izvi zvinosanganisira hukuru uye hudiki hunokosha pamwe neavhareji kuverenga uye humwe hunhu.
15. Ndeapi marudzi akasiyana eSQL JOIN mabasa aripo?
SQL inojoinha inowanzova musoro wehurukuro. Iyo INNER JOIN, RIGHT JOIN, LEFT JOIN, uye OUTER JOIN ndiwo mamwe akanyanya kukosha kuti ukwanise kudoma.
16. Rondedzera tafura yepivot.
Imwe yedzakanyanya kufarirwa nzira dzekugadzirisa data itafura yepivot. Huwandu hukuru hwe data hunounganidzwa mune maviri-dimensional tafura uchishandisa nzira iyi.
Iko kugona kukurumidza kushandura nzira iyo data inoratidzwa ndeimwe yemabhenefiti makuru epivot matafura, ayo anogona zvakare kukurumidzira maitirwo ayo vanoongorora bhizinesi vehungwaru vanogona kutora ruzivo rwakakosha kubva kumaseti akakura.
17. Unoziva here nezvedzimwe nzira dzakaita seMoSCoW neSWOT?
MoSCoW ichidimbu chinoreva kuti "Inofanira, Inofanira, Inogona, Ichaita." Kuti uise pamberi pezvinodiwa zvehurongwa, muongorori webhizinesi anofanirwa kuisa zano iri mukuita nekusiyanisa kudiwa kwega kwega nezvimwe zvinodiwa.
Semuyenzaniso, iyi chiyero ndiyo inofanirwa-kuve kana-inofanira-kuva?
Nzira inonyanya kufarirwa yekugovera zviwanikwa mumabhizinesi ndeye SWOT ongororo, inomiririra Simba, Kushaya simba, Mikana, uye Kutyisidzira.
Chero husimba hwekambani uye hutera hunofanirwa kuzivikanwa nemuongorori webhizinesi, uyo anogona kushandura izvo zvakawanikwa kuita mikana nekutyisidzira.
18. Ndeapi mabasa eUML?
Mutauro Wakabatana Wokuenzanisira, unowanzozivikanwa seUML, unopa nzira yakafanana yekufungidzira sisitimu uye iine chinangwa-chakawanda, mutauro wekuenzanisira wekusimudzira.
Kuziva uye kubvisa zvikanganiso uye mabhodhoro, inoshandiswa kururamisa maitiro ehurongwa.
19. Tsanangura ERP muhuchenjeri hwebhizimisi.
Enterprise Resource Planning, kana ERP, ndiro zita repamutemo. Mundima yehungwaru hwebhizinesi, izvi zvakakosha. Inoshandiswa kubatanidza data uye maitiro esangano mune imwechete system, kuiisa neimwe nzira.
Iko kusanganiswa kwehardware, software, uye dhatabhesi zvinogonawo kuonekwa senzira yekuchengetedza data nenzira dzakati wandei zvinoenderana nekupatsanurwa kwesangano uye zvinodiwa.
20. Panyaya yehungwaru hwebhizinesi, ungatsanangura sei SCM?
Mumusika une makwikwi anotyisa, mabhizinesi ezvitoro akatotarisana nematambudziko kubva pakukwira kuri kuita kudiwa kwechigadzirwa uye nemitengo mishoma. Nekuda kweizvi, Supply Change Management (SCM), iyo isiri yega kumafemu ekugadzira, ndiyo kiyi yekubudirira kwekambani yekugadzira.
Bhizinesi mashandiro uye mazano anotsanangurwa uchishandisa SCM. Nekudaro, kushanda nemafemu ekugadzira eSCM kunovabatsira kugadzira zvisungo zvakasimba nevatengi vavo, zvichivagonesa kupa-nguva, kutakura kwemhando yepamusoro pamutengo wakakodzera.
Uyezve, inotsigira kuenderana kwekuita.
21. Unogona here kutsanangura SRS nezvikamu zvayo zvikuru?
Sistimu kana software zvinodiwa zvinodaidzwa kunzi SRS. Iko kuunganidzwa kwemagwaro anotsanangura maitiro echidimbu chesoftware kana system.
Iine zvinhu zvakasiyana-siyana zvinodiwa nevatengi uye vanobatana kuitira kuti vanyengetedze vashandisi vekupedzisira.
Zvikamu zvikuru zveSRS ndezvi:
- Makuriro eBasa
- Dependencies
- Kufungidzira uye Zvipinganidzo
- Kubvuma Kugadziriswa
- Data Model
- Zvisiri-zvinoita uye zvinoshanda zvinodiwa
22. Rondedzera BRD. Chii chinoisiyanisa kubva kune SRS?
Bhizinesi Rinodiwa Gwaro rinonzi BRD. Icho chibvumirano chepamutemo pakati pekambani nemutengi pakusikwa kwechimwe chigadzirwa.
SRS chizvarwa cheBRD.
BRD ndeye inoshanda software yakatarwa, asi SRS chimwe chinhu icho ese maBAs anonyora mushure mekuita zvakanangana nemutengi.
Kusiyana neSRS, iyo inogadzirwa zvichibva pahunyanzvi hwehunyanzvi uye zvinodiwa, BRD inogadzirwa nemuongorori webhizinesi zvichitevera kubatana kwavo nevatengi.
23. Tsanangura pfungwa ye e-commerce maererano nehungwaru hwebhizinesi.
Izwi rekuti "e-commerce" rinoreva chiitiko chekutenga nekutengesa zvakare zvinhu nemasevhisi uchishandisa chiteshi chemagetsi, seInternet. Musanganiswa weiyo online transaction process, supply chain management system, inventory management system, EDI system, online banking system, uye masystem ekuunganidza data anoumba e-commerce system. Iyo World Wide Web inoshanda seyekutanga e-commerce chiteshi (www). Iyo Bhizinesi Intelligence inoshandiswa mune e-commerce mawebhusaiti, zvisinei, inobatsira mukusimudzira kutengesa. Izvi zvinogona kupa ruzivo rwese nezvekuwanikwa kwechigadzirwa munzvimbo imwechete, mushandisi-ane hushamwari interface, inochinjika nzira yekubhadhara, inokwezva vatengesi zvirongwa, nezvimwe.
24. Chii chaizvo chinonzi RUP methodology?
Nzira yekuvandudza mashandisirwo echigadzirwa inonzi Rational Unified Process (RUP) ine maturusi akati wandei ekubatsira mukukodha chigadzirwa chazvino uno uye mabasa akasarudzwa aine chinangwa ichi mupfungwa.
RUP inzira yakatarisana nechinhu inogonesa manejimendi anoshanda epurojekiti uye yakakwira-caliber software kugadzira.
25. Chii chaizvo chinonzi RAD methodology?
Iyo Rapid Application Development (RAD) paradigm muenzaniso weiyo yekuwedzera modhi. Zvikamu zvakasiyana zvepurojekiti zvinogadzirwa zvakazvimirira panguva imwe chete.
Kufambira mberi kweprojekiti kwakaiswa nguva, kuendeswa, uyezve kuiswa pamwechete kugadzira modhi inoshanda.
26. Unorevei chaizvoizvo nechinodikanwa? Unogona here kusiyanisa zvinodiwa nezvinodiwa?
Urongwa hwakanyanya uye humiriri hunodiwa kuti uwane zvimwe zvinangwa zvekambani. Vane chekuita vanoongorora chirongwa chisati chaitwa vachishandisa zviyero uye zvinodiwa.
Chimwe nechimwe chikamu chakanyorwa zvizere kuti chishandiswe sereferensi. Muenzaniso wakazara wemashoko uye mugumisiro unodiwa.
Semuenzaniso, iwe unofanirwa kuwana basa semuongorori webhizinesi. Unoda kutangazve, zvitupa zvedzidzo, uye ruzivo rwekubvunzurudza kuti unyorere chinzvimbo ichi.
27. Rondedzera kuchera data.
Kudhirowa kwedata inzira yekugadzirisa data uye kutora ruzivo rwunodiwa kubva mudura re data (kana data warehouse) uchishandisa akasiyana ehukama, tabular, kana multidimensional data mashandiro.
28. Ungarondedzera sei chinodikanwa sechinokwana kana kuti chakanaka?
Kana chinodiwa chikazadzisa miitiro yose mitatu yeSMART—Yakananga, Inoyerwa, Inosvikika, Yakakodzera, uye Panguva—inorangarirwa kuva yakanaka.
Kunyanya kunofanirwa kushandiswa mukutsanangurwa kwemamiriro, uye maitiro ese ebudiriro anofanirwa kuverengerwa. Chese chekushandisa chinodiwa purojekiti chinofanira kuwanikwa uye chakakodzera. Kuziviswa nenguva kwese zvirevo nemamiriro kunodiwa.
29. Chii chaizvo chinonzi executive information system (EIS)?
Chishandiso chekupa yakabatanidzwa uye yakapfupikiswa mishumo ine chekuita neazvino bhizinesi zviitiko mukati mekambani inogona kufungidzirwa seye Executive information system (EIS).
Pamusoro pezvo, EIS inopa ruzivo mune graphical interface uye yakagadzirirwa kuwedzera caliber yematekiniki anoshandiswa nepamusoro-chikamu manejimendi kukurumidza kukura kwesangano.
Inosanganisirawo nzira dzinoverengeka dzekuwana, kugadzirisa, kushandura, uye kuratidza iyo data senge graphical mishumo.
30. Chii chinonzi kunyangira, uye kunogona kudziviswa sei?
Kana chiyero chepurojekiti chikapinda zvishoma nezvishoma kupfuura zvachinoda, chinogona kunetsa, mamiriro anozivikanwa se scope creep.
Izvi zvinogona kuitika nekuda kwezvizhinji zvezvikonzero, sekugadziridzwa kwemaitiro kana zvinangwa zveprojekiti, kana zvinogona kungoitika nekuda kwekutadza kugadzirira.
Kunyangwe zvingave zvakaoma, kudzivirira kuwanda kwekukwira kwakakosha pakuchengeta purojekiti pahurongwa
. Imwe nzira yekuita izvi ndeyekuona kuti nzvimbo yeprojekiti inotsanangurwa zvakajeka uye muchidimbu kubva pakutanga uye kuti vese vanobatana vanobvumirana netsanangudzo iyi.
Kuti ive nechokwadi chekuti chero shanduko pachiyero ichinyatsoongororwa uye nekubvumirana nevose vane chekuita navo, zvakakoshawo kuve neyakatsanangurwa shanduko manejimendi maitiro munzvimbo.
Chekupedzisira asi chisiri chidiki, kuramba tichionana nevese vanobatanidzwa kunogona kubatsira kuve nechokwadi chekuti munhu wese anoziva nezvezvimhingamipinyi uye zvinangwa zveprojekiti.
31. Dimensional Modelling (DM) - chii ichocho?
DM inoshandiswa kufambisa mibvunzo yekupedzisira-mushandisi uye kugadzira nzvimbo yekuchengetera data. DM inoshandisa pfungwa mbiri dzinokosha: yekutanga i "CHOKWADI," uye yechipiri i "Dimensions."
Chirevo chacho chinosanganisirawo zviyero, izvo zvinowanzomirirwa nenhamba dzenhamba. Uye ne "zviyero" tinoreva seti yemazwi anoshandiswa kutsanangura chokwadi.
Yese nhanho yedimensional modelling process inoburitsa rumwe ruzivo, rwunogona kushandiswa kunongedzera chaizvo izvo zvinosanganisirwa mudura re data.
32. Chii chaizvoizvo chinodiwa kuisa pokutanga?
Danho rakakosha mune zvinodiwa kuunganidza maitiro ndiko kukoshesa zvinodiwa. Inovimbisa kuti zviwanikwa zvinoshandiswa nemazvo nekuisa zvakakosha kune zvinonyanya kudzvanywa zvinodiwa.
Kuisa pamberi pezvinodikanwa mune imwe hurongwa, nzira dzakasiyana dzinogona kushandiswa, kusanganisira ongororo yevatori vechikamu, kuongororwa kwemutengo-bhenefiti, uye kukosha-kwakavakirwa pamberi.
33. Iwe unotenda kuti kuedza kunofanira kusanganisira muongorori webhizimisi?
Chiyero chekubatanidzwa kwevanoongorora bhizinesi mukuyedzwa kunosiyana zvichienderana neprojekti chaiyo uye yakasimba, saka hapana mhinduro imwechete, inowanzoshanda kumubvunzo uyu.
Nekudaro, kazhinji, vaongorori vebhizinesi vanofanirwa kutora chikamu mukuyedza sezvo vachigona kupa hungwaru kuongororwa kwezvinodiwa uye kuvimbisa kuti chigadzirwa chapedzwa chinogutsa zvinodiwa nekambani.
34. Ndedzipi mhando dzakawanda dzehutungamiriri?
Kune marudzi maviri akasiyana ehierarchies:
- Default hierarchy: Iyo inoteedzana iyo iyo dimension zvinhu zvinopihwa mukirasi inoratidzwa mune zvayo.
- Customized hierarchy: Kubva pane default hierarchy, tsika yetsika inogadzirwa.
35. Tsanangura ongororo yePareto.
Kana paine zvinhu zvakati wandei zvinopa imwe nyaya kana chinangwa, ongororo yePareto inogona kushandiswa.
Iyo inonyanya kubatsira mune zvebhizinesi uye hunhu manejimendi mamiriro, apo inogona kubatsira mukuona nzvimbo dzakakosha dzekuisa pfungwa pazviri kuitira kuti uwane kuvandudzwa kukuru.
Izvo zvinodikanwa kuti utange waona ese akakodzera zvikamu wobva wazviisa maererano nekukoshera usati waita ongororo yePareto.
Ipapo chinhu chakanyanya kukosha chinobatwa, kozotevera chinonyanya kukosha, zvichingodaro.
36. Rondedzera ongororo yaKano.
Nzira yekutonga yemhando inonzi kano ongororo inobatsira makambani mukuona zvinodiwa uye zvinodiwa nevatengi vavo. Inogona kushandiswa kuwedzera matekiniki ekushambadzira, mufaro wevatengi, uye kukura kwechigadzirwa.
37. The Agile Manifesto: Chii?
Iyo Agile Manifesto muunganidzwa wemagadzirirwo esoftware anotungamira vanhu pamusoro pemaitiro uye maturusi, kutora chikamu kwevatengi pamusoro penhaurirano dzekondirakiti, uye kugadzirisa shanduko pane kuomerera kuhurongwa.
38. Gap analysis: Chii?
Nzira yakajairika mukuongorora bhizinesi ndeye gap analysis, iyo inoshandiswa kuona uye kuongorora mikaha iri pakati pechinangwa chehurongwa nekushanda kwehurongwa huripo.
Inogonawo kuonekwa sekuenzanisa kwematanho ekuita kwezvinotarirwa zviitwa uye kushanda kwazvino.
mhedziso
Unogona kubudirira mubvunzurudzo yebasa yevanoongorora bhizinesi nekushandisa zvese izvi zvakakosha zveBusiness Intelligence kubvunzurudza mibvunzo nemhinduro. Kana iwe ukadzidzira mhinduro kumibvunzo yambotaurwa, haufanirwe kuve nedambudziko kupfuudza bvunzurudzo.
Nhanho inotevera ndeyekutora matanho zvinoenderana nezvinangwa zvako. Nekugadzirira kubvunzurudzwa, tarisa Hashdork's Hurukuro Series.
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