Google Cloud expands Knowledge Catalog semantic model support, says grounding lifts agent accuracy nearly 4x

[Google Cloud] Google Cloud said its Knowledge Catalog now generally supports expanded semantic model ingestion, natively pulling semantic models and metric definitions from Looker LookML, BigQuery Graph (including BigQuery measures), dbt MetricFlow, Snowflake Semantic Views, Databricks Metric Views and SAP Core Schema Notation (CSN). The definitions are connected with schema, lineage, data profiles, business glossary and other metadata in a single context graph without moving data or rewriting business logic in a new language, according to Google Cloud. The company said internal benchmarks show grounding agents in Knowledge Catalog makes them nearly 4x more accurate, with up to 33% lower latency and up to 75% fewer tokens. When two tools define the same metric differently, both definitions appear with their provenance so data stewards can reconcile the conflict before it reaches end users, Google Cloud said.