A logical data warehouse is an architectural layer that sits atop the usual data warehouse store of persistent data. The logical layer provides several mechanisms for viewing data in the warehouse store and elsewhere across an enterprise without relocating and transforming data ahead of view time. Information Management brought this interesting information to our attention in their article, “Harnessing the value of machine learning in logical data warehouses.”
A logical warehouse also helps provide security and metadata management on top of multiple analytical data management systems. It is needed to make the data actionable because organizations often have to run multiple analytical systems due to the data volumes.
Much like how logical data warehouses can assist artificial intelligence (AI) and machine learning, machine learning technology itself can also be used to automatically tune logical data warehouses’ performance. This has proven to be a real benefit where the data that is processed in logical data warehouse queries that tend to be huge and distributed across many different systems.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.
