Does your organization have a data governance process in place? Perhaps your attempts to establish a data governance initiative have resulted in lackluster results. You’re not alone, that’s why we created a modern approach to data governance consisting of five straightforward steps to provide trusted, timely, high-quality data consistently to all users.
Learn how Fusion Consulting can help you define your data governance plan.
By defining data types, assigning names to use for reference, you will better manage data flow and integrity. Outcomes: business glossary, data relationships, reference data, business rules, policies.
Once the data types are defined, the discovery process associates data types with the reference source. Outcomes: data discovery, data profiling, data process/inventories, capabilities assessment
Creating rules to govern how data is managed improves cross-functional information integrity and inter-departmental collaboration. Outcomes: manual and automated rules, end-to-end workflows, business/IT collaboration
Over time, assessments ensure the data governance rules are capable of sustaining current data management demands. Outcomes: expectation to current stage, feedback on ROI/VOI
By proactively monitoring data quality and flow using operational dashboards, your organization will become a master of your data. Outcomes: proactive monitoring, operational dashboards, data lineage