← This weekVendor newsGovernance, catalog & semantic layerGoogle CloudLooker's semantic layer aims to bridge the gap between structured and unstructured data in AI deployments. By governing Gemini Enterprise data, it seeks to enhance user trust, particularly as LLMs face challenges with raw databases and NL2SQL models struggle with schema interpretation.
MyDataWork POV — Looker's semantic layer might promise governance, but it risks becoming a bottleneck. The reliance on NL2SQL models that 'guess' schema connections is a red flag. When these models misinterpret, they generate erratic queries and metrics, undermining the very trust they're meant to build. If Looker can't ensure consistent schema interpretation, the semantic layer could end up complicating rather than clarifying AI deployments, leaving teams with more questions than answers.
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