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Data Quality Dimensions to Ensure Optimal Data Quality

Author

Listed:
  • Svetlana Jesiļevska

Abstract

Quality is more difficult to define for data, moreover the meaning of ‘quality’ depends on the context in which it is applied. Paper gives a short overview of data quality dimensions which have been collected from literature research. This paper presents some results of expert survey on data quality issues carried out by the author. The examples illustrate the fact that it is not necessary to use all the various dimensions of data quality provided by researchers, but the most essential data quality dimensions can be combined for a specific application. To support further applications of this approach, this paper contains comparison of data quality requirements to be met from statisticians and data users point of view. The empiric method (analysis of texts and documents) and the method of theoretical research (analysis of the expert survey data) are applied.

Suggested Citation

  • Svetlana Jesiļevska, 2017. "Data Quality Dimensions to Ensure Optimal Data Quality," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 20(63), pages 89-103, March.
    • Handle: RePEc:rej:journl:v:20:y:2017:i:63:p:89-103
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    References listed on IDEAS

    as
    1. Martin J. Eppler, 2006. "Managing Information Quality," Springer Books, Springer, edition 0, number 978-3-540-32225-2, January.
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    More about this item

    Keywords

    data quality; data quality dimensions; data users;
    All these keywords.

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General

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