Abstract
Data governance methodologies have traditionally focused on control and compliance for a small subset of enterprise data (i.e., master data). The view of data as an asset and the reuse of data for a variety of analytical use cases, however, have direct implications on the way how they are governed. The CC CDQ Reference Model supports this view and outlines a three-step approach to define a data and analytics governance setup that enables value creation and innovation from data.
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Acknowledgments
This work was supported by the Competence Center Corporate Data Quality (CC CDQ, www.cc-cdq.ch). The authors would like to thank all CC CDQ partner companies for their financial support and their active contributions to the development of the Reference Model for Data and Analytics Governance.
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Legner, C., Fadler, M., Pentek, T. (2023). Data Governance Methodologies: The CC CDQ Reference Model for Data and Analytics Governance. In: Caballero, I., Piattini, M. (eds) Data Governance. Springer, Cham. https://doi.org/10.1007/978-3-031-43773-1_5
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DOI: https://doi.org/10.1007/978-3-031-43773-1_5
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