Antecedents of big data quality

Antecedents of big data quality: An empirical examination in financial service organizations

Haryadi, Adiska Fardani
Hulstijn, Joris (Tilburg University)
Wahyudi, A. (TU Delft Information and Communication Technology)
van der Voort, H.G. (TU Delft Organisation & Governance)
Janssen, M.F.W.H.A. (TU Delft Information and Communication Technology)

2017

Big data has been acknowledged for its enormous potential. In contrast to the potential, in a recent survey more than half of financial service organizations reported that big data has not delivered the expected value. One of the main reasons for this is related to data quality. The objective of this research is to identify the antecedents of big data quality in financial institutions. This will help to understand how data quality from big data analysis can be improved. For this, a literature review was performed and data was collected using three case studies, followed by content analysis. The overall findings indicate that there are no fundamentally new data quality issues in big data projects. Nevertheless, the complexity of the issues is higher, which makes it harder to assess and attain data quality in big data projects compared to the traditional projects. Ten antecedents of big data quality were identified encompassing data, technology, people, process and procedure, organization, and external aspects.

antecedents
big data
big data quality
data quality
finance

http://resolver.tudelft.nl/uuid:97da1a44-d621-4f28-9ff5-6568b4b18865

https://doi.org/10.1109/BigData.2016.7840595

Institute of Electrical and Electronics Engineers (IEEE)

9781467390040

Proceedings of 2016 IEEE International Conference on Big Data, Big Data 2016

4th IEEE International Conference on Big Data, Big Data 2016, 2016-12-05 → 2016-12-08, Washington, United States

Institutional Repository

conference paper

© 2017 Adiska Fardani Haryadi, Joris Hulstijn, A. Wahyudi, H.G. van der Voort, M.F.W.H.A. Janssen