Understanding ETL and Data Warehousing: Issues, Challenges and Importance

Jaiteg Singh

ISBN 10: 3843390932 / ISBN 13: 9783843390934

Published by LAP LAMBERT Academic Publishing Jan 2011, 2011

About this Item

Neuware -Testing in data warehouse systems is substantial because it is oriented towards the correctness and validation of data/ information supplied for decision making. Keeping in view the idiosyncratic characteristics of data warehouse testing and the complexity of data warehouse projects, this research has reviewed and revised the scope of automated testing in assuring quality data warehouse solutions. Initially a data set generator has been developed to generate synthetic but near to real data; followed by the classification of anomalies in synthesized data with the help of a hand coded Extraction, Transformation and Loading (ETL) routine. To ensure quality data for a data warehouse and to promulgate the importance of Extraction, Transformation and Loading (ETL) routines some test cases of prime importance were identified. Later on automated testing procedures were embedded in hand coded ETL routine to ensure quality data. The statistical analysis revealed major enhancement in data quality with the introduction of automated testing procedures. The various data warehouse architectures have been analyzed to endorse a refined data warehouse architecture named as Data Sharehouse.Books on Demand GmbH, Überseering 33, 22297 Hamburg 204 pp. Englisch.

Seller Inventory # 9783843390934

Bibliographic Details

• Title: Understanding ETL and Data Warehousing: Issues, Challenges and Importance
• Publisher: LAP LAMBERT Academic Publishing Jan 2011
• Publication Date: 2011
• Language: English
• ISBN 10: 3843390932
• ISBN 13: 9783843390934
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

Testing in data warehouse systems is substantial because it is oriented towards the correctness and validation of data/ information supplied for decision making. Keeping in view the idiosyncratic characteristics of data warehouse testing and the complexity of data warehouse projects, this research has reviewed and revised the scope of automated testing in assuring quality data warehouse solutions. Initially a data set generator has been developed to generate synthetic but near to real data; followed by the classification of anomalies in synthesized data with the help of a hand coded Extraction, Transformation and Loading (ETL) routine. To ensure quality data for a data warehouse and to promulgate the importance of Extraction, Transformation and Loading (ETL) routines some test cases of prime importance were identified. Later on automated testing procedures were embedded in hand coded ETL routine to ensure quality data. The statistical analysis revealed major enhancement in data quality with the introduction of automated testing procedures. The various data warehouse architectures have been analyzed to endorse a refined data warehouse architecture named as Data Sharehouse.

About the Author

Name: Jaiteg Singh (MCA, M.Phil (Comp.Sci.), Ph.D (Comp.Sci. & Engg) Area of Interest: Software Engineering, Data Warehousing