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Author:Hänninen, Sami
Title:Applying data mining techniques to ERP system anomaly and error detection
Tiedonlouhinnan soveltaminen ERP -järjestelmän poikkeamien ja virheiden havaitsemiseen
Publication type:Master's thesis
Publication year:2010
Pages:x + 66      Language:   eng
Department/School:Elektroniikan, tietoliikenteen ja automaation tiedekunta
Main subject:Tietokoneverkot   (T-110)
Supervisor:Ylä-Jääski, Antti
Instructor:Kiravuo, Timo ; Veikkola, Olli
Electronic version URL: http://urn.fi/URN:NBN:fi:aalto-201203131446
OEVS:
Electronic archive copy is available via Aalto Thesis Database.
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Location:P1 Ark Aalto  797   | Archive
Keywords:data mining
database
ERP
KDD
input validation
Oracle
Lean System
ODM
data quality
tiedonlouhinta
tietokanta
ERP
KDD
syötteen tarkistus
Oracle
Lean System
ODM
tiedon laatu
Abstract (eng): Data mining is a concept developed for analyzing large quantities of data.
It is based on machine learning, pattern recognition and statistics and is currently used, for example, for fraud detection, marketing advice, predicting sales and inventory and correcting data.
Enterprise Resource Planning (ERP) systems commonly gather data from all parts of company operations thus providing a good source of data for data mining.

This thesis studies data mining suitability for real-time validation of Lean System ERP input on the Oracle Data Mining (ODM) platform to improve data quality.
The results proved that data mining can be a successful tool for input validation, but a successful mining process requires often meticulous pre-processing of mined data and good knowledge of the algorithms.
Abstract (fin): Tiedonlouhinta kehitettiin oleellisen tiedon löytämiseen suurista tietomassoista ja pohjautuu koneoppimiseen, hahmontunnistukseen ja tilastotieteeseen.
Suosittuja käyttökohteita ovat esimerkiksi huijausten havainnointi, markkinointianalyysit, myynnin ja varaston ennustaminen sekä tietojen korjaus.
Toiminnanohjausjärjestelmät (ERP) keräävät suuria määriä tietoja kaikista yrityksen toiminnoista, mikä tekee niistä hyvän kohteen tiedonlouhinnalle.

Tämä diplomityö tutkii tiedonlouhinnan sopimista Lean System toiminnanohjausjärjestelmän syötteiden tarkistukseen tosiaikaisesti Oraclen tiedonlouhinta-alustalla tiedon laadun parantamiseksi.
Tulokset osoittavat, että tiedonlouhinta voi olla menestyksekäs työkalu syötteen tarkistukseen, mutta onnistunut louhintaprosessi vaatii usein louhittavan tiedon pikkutarkkaa esikäsittelyä ja algoritmien hyvää tuntemusta.
ED:2010-07-15
INSSI record number: 39966
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