Data governance in big data platforms

Julia Bardmesser, Ian Maung and Olga Maydanchik

Journal of Digital Banking, 2017, vol. 2, issue 1, 22-32

Abstract: During the past decade many financial companies have invested heavily in big data. The promise of this technology, of being able to analyse vast amounts of data quickly and obtain previously unavailable insights about the customers, trends and future opportunities, is remarkable. However, it has become clear that it is not enough to throw all the available data together and run the latest visualisation software on it. To build a business strategy based on this intelligence something more is needed – trust in the data on which the intelligence is obtained. Data governance is an important enabler of this trust. This paper considers in depth how data governance becomes an important enabler of effective use of big data platforms in financial services companies by examining three major use cases of big data environments: ad hoc analytics and visualisation, online data archival and business critical applications. By thorough examination of the essential dimensions of data governance, the paper builds a framework that can guide the management of the companies in their decisions on the appropriate uses of big data platforms and the corresponding investment in the necessary levels of data governance.

Keywords: big data; data governance; data management; data analytics; metadata; ontology; data quality; data architecture; data (search for similar items in EconPapers)
JEL-codes: E5 G2 (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:aza:jdb000:y:2017:v:2:i:1:p:22-32

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