Optimizing Efficiency with Split Data Models Splitting thin reports from data models in PowerBI creates a single source of truth while reducing storage costs. Multiple reports can seamlessly connect to one dataset, boosting consistency and efficiency. Segregating data models from report visuals enhances security by allowing distinct access controls, and it enables parallel work for specialists in data modeling and report design.
Enhancing Security and Governance Isolating datasets in a dedicated workspace allows broader access for business users to reports while keeping the underlying data strictly controlled. This separation enforces robust governance and minimizes risks tied to data manipulation. The method streamlines enterprise reporting, ensuring that permission policies are appropriately distributed between data maintenance and visualization teams.
Automating the Separation Process with Modern Tools Microsoft Fabric and Semantic Link Labs simplify what was once a complex manual process by automating dataset relocation, report rebind, and optional deletion of the original model. A Python-driven solution installs necessary tools, then moves the dataset to the appropriate workspace and reconnects the report to the new source with only three straightforward commands. Demonstrative code on handling example dashboards showcases how quickly production workspaces can evolve to hold only thin reports while datasets remain secure elsewhere.