DocumentCode
2569265
Title
Alliance Rules for Data Warehouse Cleansing
Author
Arora, Rajiv ; Pahwa, Payal ; Bansal, Shubha
Author_Institution
Dept. of IT, GPMCE, Delhi, India
fYear
2009
fDate
15-17 May 2009
Firstpage
743
Lastpage
747
Abstract
Data cleansing is an activity performed on the data sets of data warehouse to enhance and maintain the quality and consistency of the data. This paper addresses the problems related with dirty data, entrance of dirty data and detection of dirty data in the data warehouse. The paper perceives the procedure of data cleansing from a different perspective. It provides an algorithm for the detection of errors and dirty data in the data sets of an already existing data warehouse. The paper characterizes the alliance rules based on the concept of mathematical association rules to determine the dirty and faulty data in data warehouse. The research marks the use of q-grams to determine the errors in a prominent way.
Keywords
data analysis; data integrity; data mining; data warehouses; set theory; alliance rule; data cleansing; data consistency; data set error detection; data warehouse; dirty data detection; faulty data; mathematical association rule; Association rules; Data mining; Data warehouses; Decision making; Degradation; Enterprise resource planning; Performance analysis; Signal processing; Signal processing algorithms; Strategic planning; data cleansing; data marts; data warehouse;
fLanguage
English
Publisher
ieee
Conference_Titel
2009 International Conference on Signal Processing Systems
Conference_Location
Singapore
Print_ISBN
978-0-7695-3654-5
Type
conf
DOI
10.1109/ICSPS.2009.133
Filename
5166887
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