Data quality and regulations are perpetual drivers for Data Governance solutions that systematically monitor the execution of data policy. And yet, there is along road ahead to achieve Data Governance: the term is still relatively unknown, there is no political forum in the form of a Data Governance Council, and software support is moderate. Time for change ! Data Governance requires automation on the one hand and a wide adoption of business to ICT on the other.
In this lecture, we set out the basic principles to successful develop Data Governance. By way of example, we show how to translate this in Collibra's Data Governance Center. We pay particular attention to identifying and modelling data policies and rules, and to empowering them on the basis of data stewardship and configurable workflows across silos and functions in the organization. The example is drawn from the Flanders Research Information Space, where data quality is critical to drive and boost pan-European Research policy.