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Comparative Study of Data Quality Dimensions for Data Warehouse Development: A Survey

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Advanced Machine Learning Technologies and Applications (AMLTA 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 322))

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Abstract

Due to the increasing complexity of data warehouse (DW), continuous attention must be paid for evaluation of their quality throughout their design and development. DW quality depends on the quality of all requirements, conceptual, logical and physical models used for DW design. Therefore, identification of various data quality (DQ) dimensions in those phase of DW development are very much needed.

In this paper, we surveyed and evaluated the literature related to the DQ dimension in every phase of DW development and proposed an integrated approach for incorporating DQ in DW development in order to minimize risk of DW project failure.

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Author information

Authors and Affiliations

  1. Dept. of Information System, Universiti Teknology Malaysia, Johor Bahru, Malaysia

    Munawar, Naomie Salim & Roliana Ibrahim

Authors
  1. Munawar
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  2. Naomie Salim
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  3. Roliana Ibrahim
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Editor information

Editors and Affiliations

  1. Cairo University, Egypt

    Aboul Ella Hassanien  & Rabie Ramadan  & 

  2. Ain Shams University, Cairo, Egypt

    Abdel-Badeeh M. Salem

  3. University of Tasmania, TAS, Australia

    Tai-hoon Kim

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Munawar, Salim, N., Ibrahim, R. (2012). Comparative Study of Data Quality Dimensions for Data Warehouse Development: A Survey. In: Hassanien, A.E., Salem, AB.M., Ramadan, R., Kim, Th. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2012. Communications in Computer and Information Science, vol 322. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35326-0_46

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  • DOI: https://doi.org/10.1007/978-3-642-35326-0_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35325-3

  • Online ISBN: 978-3-642-35326-0

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