Logical Data Warehouse

Analytical data architecture that optimizes diverse data sources and use cases

In most organizations, as data and analytics needs evolve, so does the infrastructure to support them. This practice has led to a variety of fit-for-purpose, physical data management approaches: data warehouses, data marts, sandboxes, data lakes, and more, either in the cloud or on-premises. And the resulting data silos have made it difficult to drive needed insights. Pragmatic companies are implementing logical data warehouse architecture that lets them meet ever-changing requirements without stranding past investments.