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A Process Pattern Model for Tackling and Improving Big Data Quality

Author

Listed:
  • Agung Wahyudi

    (Delft University of Technology)

  • George Kuk

    (Nottingham Trent University)

  • Marijn Janssen

    (Delft University of Technology)

Abstract

Data seldom create value by themselves. They need to be linked and combined from multiple sources, which can often come with variable data quality. The task of improving data quality is a recurring challenge. In this paper, we use a case study of a large telecom company to develop a generic process pattern model for improving data quality. The process pattern model is defined as a proven series of activities, aimed at improving the data quality given a certain context, a particular objective, and a specific set of initial conditions. Four different patterns are derived to deal with the variations in data quality of datasets. Instead of having to find the way to improve the quality of big data for each situation, the process model provides data users with generic patterns, which can be used as a reference model to improve big data quality.

Suggested Citation

  • Agung Wahyudi & George Kuk & Marijn Janssen, 2018. "A Process Pattern Model for Tackling and Improving Big Data Quality," Information Systems Frontiers, Springer, vol. 20(3), pages 457-469, June.
    • Handle: RePEc:spr:infosf:v:20:y:2018:i:3:d:10.1007_s10796-017-9822-7
    DOI: 10.1007/s10796-017-9822-7
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    References listed on IDEAS

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    Cited by:

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    2. Roman Lukyanenko & Andrea Wiggins & Holly K. Rosser, 0. "Citizen Science: An Information Quality Research Frontier," Information Systems Frontiers, Springer, vol. 0, pages 1-23.
    3. Qi Liu & Gengzhong Feng & Giri Kumar Tayi & Jun Tian, 2021. "Managing Data Quality of the Data Warehouse: A Chance-Constrained Programming Approach," Information Systems Frontiers, Springer, vol. 23(2), pages 375-389, April.
    4. Amit V. Deokar & Jie Tao, 0. "OrgMiner: A Framework for Discovering User-Related Process Intelligence from Event Logs," Information Systems Frontiers, Springer, vol. 0, pages 1-20.
    5. Yogesh K. Dwivedi & Gerald Kelly & Marijn Janssen & Nripendra P. Rana & Emma L. Slade & Marc Clement, 2018. "Social Media: The Good, the Bad, and the Ugly," Information Systems Frontiers, Springer, vol. 20(3), pages 419-423, June.
    6. Amit V. Deokar & Jie Tao, 2021. "OrgMiner: A Framework for Discovering User-Related Process Intelligence from Event Logs," Information Systems Frontiers, Springer, vol. 23(3), pages 753-772, June.
    7. Roman Lukyanenko & Andrea Wiggins & Holly K. Rosser, 2020. "Citizen Science: An Information Quality Research Frontier," Information Systems Frontiers, Springer, vol. 22(4), pages 961-983, August.

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