A data engineering team is spreading data across a Hadoop-based data lake and a warehouse-powered BI platform, and wants analysts to query all of it consistently without dealing with the underlying system complexity. Which architectural approach directly addresses this goal?
Explanation
A data fabric is a unified data integration and management layer that serves as the connective tissue between cloud and on-premises data endpoints
A data fabric should ultimately abstract away the underlying complexity of the heterogeneous systems that it interconnects
In the context of a data fabric, what distinguishes active metadata from passive metadata, and how is the conversion between them achieved?
Explanation
AI and ML convert passive metadata to active metadata by continuously analyzing metadata
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