Telecommunications executives are widely adopting AI, but many initiatives stall due to poor data governance and fragmented data landscapes, not model limitations.
- •The primary challenge is 'data debt' — fragmented, ungoverned data that lacks semantic clarity across disparate systems
- •A semantic layer is essential to unify data sources, enforce consistent governance, and enable AI agents to access reliable, contextualized information
- •Databricks Unity Catalog addresses these challenges through Delta Sharing for cross-organization data exchange, Lakeflow Connectors for managed ingestion, and Lakehouse Federation for querying external systems
- •Unified governance policies including attribute-based access control, workspace bindings, and dynamic masking ensure compliance and data security
This summary was automatically generated by AI based on the original article and may not be fully accurate.
Databricks
Google Cloud