Research Article Open Access

Using Metadata Analysis and Base Analysis Techniques in Data Qualities Framework for Data Warehouses

Azwa Abdul Aziz1, Md Yazid Mohd Saman1 and Mohd Pouzi Hamzah1
  • 1 University Sultan Zainal Abidin (UniSZA), Malaysia


Information provided by any applications systems in organization is vital in order to obtain a decision. Due to this factor, the quality of data provided by Data Warehouse (DW) is really important for organization to produce the best solution for their company to move forwards. DW is complex systems that have to deliver highly-aggregated, high quality data from heterogeneous sources to decision makers. It involves a lot of integration of sources system to support business operations. Problem statement: Many of DW projects are failed because of Data Quality (DQ) problems. DQ issues become a major concern over decade. Approach: This study proposes a framework for implementing DQ in DW system architecture using Metadata Analysis Technique and Base Analysis Technique. Those techniques perform comparison between target values and current values gain from the systems. A prototype using PHP is develops to support Base Analysis Techniques. Then a sample schema from Oracle database is used to study differences between applying the framework or not. The prototype is demonstrated to the selected organizations to identify whether it will help to reduce DQ problems. Questionnaires have been given to respondents. Results: The result show user interested in applying DQ processes in their organizations. Conclusion/Recommendation: The implementation of the framework suggested in real situation need to be conducted to obtain more accurate result.

American Journal of Economics and Business Administration
Volume 3 No. 1, 2011, 112-119


Submitted On: 12 March 2009 Published On: 31 January 2011

How to Cite: Aziz, A. A., Saman, M. Y. M. & Hamzah, M. P. (2011). Using Metadata Analysis and Base Analysis Techniques in Data Qualities Framework for Data Warehouses. American Journal of Economics and Business Administration, 3(1), 112-119.

  • 2 Citations



  • Data Warehouse (DW)
  • Data Quality (DQ)
  • metadata Analysis
  • DQ dimension