Mitmetasandiliste protsesside ennustav seire

dc.contributor.advisorLeontjeva, Anna
dc.contributor.advisorDumas, Marlon
dc.contributor.authorTrees, Henri
dc.date.accessioned2017-04-26T07:01:24Z
dc.date.available2017-04-26T07:01:24Z
dc.date.issued2016
dc.description.abstractInfosüsteemide laialdane kasutamine järjest rohkemates valdkondades tekitab aina suuremaid salvestatavaid andmemahte. Organisatsioonide ja äride efektiivsuse kasvuga tekib suurem vajadus leida alternatiivseid viise konkurentsieelisteks. Järjest rohkem hakatakse antud infoajastul otsima ärilist väärtust andmetest. Protsessikaeve meetodeid kasutades üritatakse justnimelt seda teha, kuid äriprotsesside arenedes muutuvad keerukamaks ka andmed, mis neid protsesse kirjeldavad. Hetkel keskendutakse protsessikaeve uurimustes protsessidele, mida on võimalik väljendada järjestikkuste sündmuste jadana. Käesolevas magistritöös esitatakse uudne lähenemine äriprotsesside ennustava seire rakendamiseks mitmetasandilistele äriprotsessidele, mis sisaldavad paralleelseid alamprotsesse ning mida pole võimalik sündmuste järjendina väljendada. Väljapakutud meetodi suutlikkuse hindamiseks rakendatakse antud meetodit elulisel andmestikul telekommunikatsiooni tegevusalalt. Tulemusi võrreldakse lähenemisega, mida kasutatakse ühetasandiliste äriprotsesside ennustavaks seireks.
dc.description.abstractThe ever increasing use of Information Systems causes ever more information to be stored. As organizations and businesses become more efficient due to competition they need to gain competitive advantage over others. More and more companies and institutions have turned to Information Technology to find business value in a data-driven world. Modern Information Systems maintain records of process events, which correspond to real-life activities. As processes evolve and become more complex, so does the information that reflects them. In this thesis, we propose an approach to predictive monitoring of complex multi-level processes. In this context, a multi-level process consists of a high-level parent process which spawns multiple low-level subprocesses, which have their own life cycle and run independently of one another. The author proposes constructs called milestones, which include both parent- and subprocesses and are used for the predictive monitoring classification task. This approach has been validated on a real-life event log of the business-to-business change management process in place at Baltic's largest telecommunications company Telia Estonia.
dc.identifier.urihttp://hdl.handle.net/10062/56149
dc.language.isoeng
dc.titleMitmetasandiliste protsesside ennustav seire
dc.title.alternativePredictive Monitoring of Multi-level Processes
dc.typeThesis

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