Alliance Rules for Data Warehouse Cleansing

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 pro...

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Bibliographic Details
Published in2009 International Conference on Signal Processing Systems pp. 743 - 747
Main Authors Arora, R., Pahwa, P., Bansal, S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2009
Subjects
Association rules
data cleansing
data marts
Data mining
data warehouse
Data warehouses
Decision making
Degradation
Enterprise resource planning
Performance analysis
Signal processing
Signal processing algorithms
Strategic planning
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Summary: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.
ISBN:9780769536545
0769536549
DOI:10.1109/ICSPS.2009.133