DataHub Blog
Insights on context management and how the best data and AI teams are using DataHub.
-
Context Management Is the Missing Piece in the Agentic AI Puzzle
Context management gives AI agents secure, reliable access to enterprise data. Learn what it is and how to implement it.
Popular Posts
-
DataHub: The Semantic Backbone of Enterprise Data Analytics Agents
Last week, the Pinterest engineering team published an incredibly thorough deep dive about how they built the most widely adopted AI agent at…
-
Ask DataHub
Find data faster, debug quality issues, and generate accurate SQL with Ask DataHub — the AI assistant built into DataHub
-
Data Products: From Concept to Implementation
The argument for treating data as a product has already been fought and won: The industry agrees. Analysts have written the frameworks, conference…
-
Introducing DataHub Cloud v0.3.17
DataHub Cloud v0.3.17 brings native Microsoft Fabric connectors for cross-platform lineage, Ask DataHub Plugins for multi-tool context, and smarter data quality monitoring.
-
Part 2: How to Implement Data Mesh (Without Replacing One Bottleneck With Another)
Learn how Foursquare uses H3 indexing, Spatial Desktop, and an AI-powered Spatial Agent with DataHub as the discovery engine for geospatial datasets.
-
Part 1: What Is Data Mesh? Architecture, Principles, and Why It Matters for AI
Learn how Foursquare uses H3 indexing, Spatial Desktop, and an AI-powered Spatial Agent with DataHub as the discovery engine for geospatial datasets.
-
Data Lineage: What It Is and Why It Matters
Data lineage tracks where data comes from, how it transforms, and where it ends up. Learn why it matters and how to implement…
-
How Foursquare Uses DataHub for Geospatial Dataset Discovery
Learn how Foursquare uses H3 indexing, Spatial Desktop, and an AI-powered Spatial Agent with DataHub as the discovery engine for geospatial datasets.
-
Part 2: How DataHub MCP Closes the Context Gap
Learn how DataHub closes the context gap for MCP-connected AI agents—giving them the lineage, ownership, and quality signals they need to move from…
-
Part 1: What Is an MCP Server? Model Context Protocol Explained
Learn what an MCP server is, how the Model Context Protocol works, and why AI agents need more than connectivity to be production-ready.
-
Accelerating Connector Development with AI Skills
Explore February’s DataHub Town Hall: learn how AI skills help build connectors in hours, see Foursquare’s spatial agent, and preview the 2026 roadmap.
-
The Data Engineer’s Guide to Context Engineering
Context engineering needs your data engineering skills. Learn how metadata, governance, and pipeline expertise translate to building context for AI agents.
