Pioneering a New Data Architecture for AI: CData Semantic Layer Meets Databricks Genie

A CData Foundations session featuring FinThrive’s Andrew Chabot and Databricks’ Eric Tome described how Databricks and CData can jointly support enterprise AI initiatives by combining scalable data engineering, governance, analytics, and AI capabilities with broad data accessibility. Databricks consolidates, cleans, and prepares data from numerous operational systems, while CData’s virtualized semantic layer presents disparate sources as standardized, governed assets that can be consumed by Databricks and accessed through business tools such as Tableau, Power BI, and Excel without custom exports or additional pipelines. The speakers highlighted that this approach can reduce ETL work, shorten reporting and experimentation cycles, and allow business users to work with live, curated data while engineers retain governance and optimization in the lakehouse. A demonstration showed datasets such as assets, locations, and sensors appearing as native Databricks tables, then being made available for real-time analysis and operational workflows. The partnership was presented as complementary: Databricks provides the compute and AI foundation, while CData accelerates data integration, virtualization, and delivery of insights across the organization.

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