ON-DEMAND DEMO

How Data Platform Admins Configure the DataHub Context Pipeline

Someone has to build the pipeline that makes the context platform work. This session shows data platform engineers how to configure DataHub Cloud end to end: connecting sources, running AI context generation, routing proposals to domain owners, and validating accuracy with the Eval Suite.

What you’ll learn

How to connect sources like Snowflake, BigQuery, dbt, and Looker and configure scheduled ingestion
How to run a context generation job that scans your catalog and drafts descriptions using AI
How to route proposals to the right domain experts for review via Slack and track approval status
How to define benchmark questions in the Eval Suite and catch context drift before it reaches analysts

Watch the Demo

More Demos

View All Demos

DEMO09.02.26

SME Feedback in Claude for Continuously Trusted Context

See how DataHub Cloud enables subject matter experts to correct outdated context directly inside Claude and watch the fix automatically route to the right domain owner, update the context layer, and propagate everywhere.

DEMO09.02.26

Context Hub: Where Expert Knowledge Becomes Agent-Ready Context

See how DataHub Cloud's Context Hub gives domain experts a workspace to review AI-proposed context, resolve conflicting definitions, simulate the impact on text-to-SQL results, and publish with confidence.

DEMO09.02.26

How DataHub Cloud Generates a Semantic Index from Enterprise Query History

See how DataHub Cloud's Context Intelligence mines years of enterprise query history to generate a semantic index with no manual semantic modeling required. Watch coverage go from near zero to production-ready in minutes.