Fig.1 Data-centric projects seek to extract value from already existing production data. By contrast, process-centric projects try to automate a process. IT traditionally thinks in a process-centric way. We need Data Governance to ensure knowledge about data is captured during a data-centric project, rather than just assumed, and that it is preserved for future reuse.
BUILD YOUR ORGANIZATION’S DATA GOVERNANCE FUNCTION BASED ON THE MOST SUITABLE OPERATING MODEL.
PRIORITIZE AND DEVELOP SPECIFIC DATA GOVERNANCE CAPABILITIES BASED ON OUR DATA GOVERNANCE FRAMEWORK.
SUCCESSFULLY DEVELOP AND INTRODUCE DATA POLICIES AND STANDARDS.
INTEGRATE DATA GOVERNANCE WITH CLOSELY RELATED FUNCTIONS LIKE: IT, ENTERPRISE ARCHITECTURE, LEGAL, HUMAN RESOURCES, AND INTERNAL AUDIT TO AVOID CONFLICTS AND ENSURE NOTHING FALLS BETWEEN THE CRACKS.
UNDERTAKE ORGANIZATIONAL CHANGE MANAGEMENT FOR DATA GOVERNANCE, IMPROVING DATA LITERACY AND ESTABLISHING A DATA CULTURE, INCLUDING A CAREFULLY CRAFTED COMMUNICATIONS STRATEGY.
THE BENEFITS TO BE REALIZED FROM DATA GOVERNANCE ARE NOTHING LESS THAN THE ABILITY TO SURVIVE AND THRIVE IN THE INFORMATION AGE.
Fig. 2 Data Governance has many diverse elements. The point is not to be overwhelmed by all of it, but to recognize what has to be prioritized and to build capacities that are sufficient for the organization’s needs, but no more.