Data modeling workflows need to be predictable. Whether teams are importing models through the command line, running workflow scripts, applying Model Conversion Rules or editing multiple entity columns at once, they need confidence that every step can be monitored,...
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Enterprise Data Modeling: Turning Architecture Into the Metadata Control Plane for AI-Ready Data
Enterprise data modeling is no longer just a design exercise. For years, data models helped architects define entities, relationships, keys, attributes and structures before implementation. That work still matters. Conceptual, logical and physical models remain...
Replacing SAP PowerDesigner: A Practical Data Modeling Migration Path
For many enterprise data teams, SAP PowerDesigner has been part of the data architecture toolkit for years. It has supported conceptual data models, logical data models, physical data models, warehouse modeling, reverse engineering, impact analysis and database design...
Choosing a Modern Data Modeling Platform: Design Warehouses, Lakes, and Lakehouses with Confidence
Modern data estates have outgrown the whiteboard. The diagrams that once captured a single warehouse now have to describe dozens of sources, multiple cloud platforms and a web of regulatory obligations that change faster than most teams can document them. When a...
Why Data Warehouse Projects Fail After They Go Live
Building a data warehouse is hard, sure. But making sure it stays useful is even harder. Many data warehouse projects are judged on the launch … did the team connect the right sources, build the models, create the dashboards and deliver the first round of reporting?...
How-to: Design Data Architectures That Adapt as You Evolve
Data architectures rarely fail because they were wrong on day one. More often, they fail later, when the business changes faster than the architecture can keep up. New source systems arrive. Definitions change. Mergers happen. Reporting requirements expand. Platforms...
What We Discovered at Data Innovation Summit 2026: AI Readiness, Migration & Modern Data Stacks
When we flew northbound to attend the Data Innovation Summit, DIS 2026, in Stockholm, we expected AI to dominate the conversation. And it did. But the most intriguing conversations were not about AI in isolation. Rather, they were about what needs to sit underneath...
New in 3D 9.0.6.3: The ‘Data Integrity’ Release
Data modeling depends on trust. If the model does not preserve the right relationships, transformations, mappings and profiling context, teams lose confidence in what they are building. WhereScape 3D 9.0.6.3 focuses on that trust layer: improving data integrity,...
What We Learned About Higher Education Data at HEDW 2026
The WhereScape team recently attended the 2026 HEDW Conference in Austin, Texas, held April 26 - 29th, 2026. HEDW describes itself as a community focused on knowledge management in colleges and universities, including data warehouses, institutional reporting...








