1. Ho hatisoa ho boletsoeng esale pele (ho fapana le ho hlalosa, ho hlophisa kapa ho kopanya)

2.Tlhahlobo e potlakileng e lekantsoeng ka lihora kapa matsatsi (ho fapana le likhoeli tse stereotypical tsa setso tlhahisoleseling)

3. Ho hatisoa bohlokoa ba litaba tsa khoebo (ha ho litlhahlobo tsa tora ea lenaka la tlou)

4. Ho hatisa (ho eketsa) ts'ebeliso e bonolo, ka hona ho etsa hore lisebelisoa li fihlellehe ho basebelisi ba khoebo

Litlhahlobo tsa Predictive o sebedisa dithekniki tse fapaneng ho nts'etsapele meetso ea ponelopele le ho thusa ho noha leseli le lipaterone.
Ho sebelisa leseli lena, likhoebo li khona ho utloisisa basebelisi ba tsona hantle le ho tsamaisa liqeto tsa leano la ho theha boiphihlelo bo ikhethileng, bo ikhethileng le boqapi ba moreki nakong eohle ea bophelo ba bareki.

Mahlale a morao-rao a data a bapala karolo ea bohlokoa ho li-analytics tsa ponelopele kaha ba fana ka bohlale mabapi le bokamoso ba sebelisa leseli la Big Data. Mahlale a morao-rao a Big Data a sekaseka boholo ba data ka nako ea 'nete, ho kenyeletsoa le tlhaiso-leseling e sa hlophisoang, mme leseli le fumanoeng tlhahlobisong ena le ka sebelisoa ho ntlafatsa ts'ebetso ea ts'ebetso, ho lekola menyetla e mecha ea lekhetho le melemo ea tlholisano. Big tlhahlobo ea data software e etselitsoe ho sebetsana le liforomo tse kholo tsa data, tse nang le meralo ea motheo, pono, pono, tsamaiso le lera la analytics. Lera la analytics ke karolo ea mantlha ea moaho li-analytics tsa ponelopele tharollo ho meralo e kholo ea data ea khoebo. Litlhahlobo tsa Predictive e hlwaya mekhoa e nang le moelelo ea lintlha tse kholo ho bolela liketsahalo tsa kamoso le ho lekola bokhoni ba liphetho tse fapaneng tse ka bang teng e le hore likhoebo li ka etsa liqeto tse bohlale

Ho na le lik'hamphani tse ngata tse sebetsang Litlhahlobo tsa Predictive. Sena ha se ba thuse feela ho hlahloba menyetla e mecha ea 'maraka, ho ntlafatsa ts'ebetso ea ts'ebetso ea ts'ebetso ea khoebo, ho matlafatsa botšepehi ba bareki le ho li boloka empa hape li li nolofalletsa ho tseba hantle mokhoa oa sepheo sa moreki le ho hlahloba mefuta e mecha ea khoebo. Melemo e meng e bontšang khoebo ke

1. Eketsa letseno la thekiso
2. Eketsa sekhahla sa karabelo ea phutuho
3. Fokotsa tšebeliso ea chelete ea ho bapatsa
4. Fokotsa churn ea bareki
5.Ho eketsa tšebeliso ea bareki, ho e boloka le ho ts'epahala jj
6. Litlhahlobo tsa Predictive Lisebelisoa:
7. Lisebelisoa tse ngata tse fapaneng li sebelisoa ho etsa mohlala oa li-predictive le li-analytics. Mabitso a mang a tummeng a barekisi 'marakeng ke:

Mohloli o Hlahileng:
R, Apache Spark, HP Haven Litlhahlobo tsa Predictive, Actian Vortex Express, Konstanz Information Miner.

Mong'a ntlo:
SAS, IBM, SAP

Software APIs:
Google Prediction API, Microsoft Azure Machine Ithuta, BigML, PonelopeleIO

Litsela tsa bohlokoa:

Tsepamisa maikutlo ho bolela lintho esale pele / mekhoa le ponelopele ho fapana le ho bokella tlhaiso-leseling, tlhophiso le ho kopanya.
Ponelopele le ponelopele e potlakileng ea nako ka ho nka liqeto mabapi le leseli la morao-rao le la moraorao
Utloisisa sepheo sa ho qetela sa Litlhahlobo tsa Predictive bakeng sa mokhatlo.
Hlalosa mokhoa oa ho li hlophisetsa ho Predictive Enterprise
Boloka basebelisi ba khoebo ba sebelisana le eng Litlhahlobo tsa Predictive e ka ba thusa ho finyella.