Topic
semantic layer
17 posts tagged “semantic layer”.
-
Apache Ossie and Apache Polaris: Putting Semantic Models in the Open Catalog
Ask four systems in the same company what "monthly active users" means and you get four answers. The BI tool counts distinct user IDs with at least…
-
Metric Contracts in Code: Testing, Versioning, and Serving Business Logic to Multi-Agent Systems
Three agents answer the same question on the same afternoon. A finance agent, asked for last quarter's net revenue, sums completed orders, subtracts…
-
Semantic Layer Federation: One Logical Model Over Data on Three Clouds
A global retailer's revenue dashboard needs four sources. Orders are in an Apache Iceberg table on S3 in Virginia. Customers are in an Iceberg table…
-
The Five Layers of an Agentic Lakehouse
Every architecture era gets its reference diagram. The warehouse era had its star schemas and its staging-to-mart flow. The big data era had its…
-
Metric Contracts in 2026: Standardizing Business Logic Across Multi-Agent Frameworks
For twenty years, the cost of an ambiguous metric was a meeting. Two dashboards disagreed, two teams defended their numbers, someone scheduled the…
-
Semantic Layer Federation: One Meaning for Data That Lives Everywhere
Ask three systems in the same company what monthly recurring revenue was in July and you can get three answers, each computed correctly by its own…
-
Why Agentic AI Needs a Governed Semantic Layer Behind the Model Context Protocol
An executive asks an AI assistant what revenue looked like last quarter. The assistant writes SQL against the warehouse, sums an amount column, and…
-
Metric Contracts as the Interface AI Agents Actually Need
Two teams present in the same meeting. Sales says pipeline conversion is 24 percent. Finance says it is 19. Both numbers came from the same…
-
Why AI Agents Fail on Raw Data, and What to Give Them Instead
An analytics agent gets read access to the data lake. Someone asks it for last quarter's revenue by region. It finds a table named factorders, writes…
-
The Five Layers Between Your Lakehouse and a Trustworthy Agent
An organization ships an analytics agent. It has access to the warehouse, a good model, and a well-written system prompt. Three weeks in, it has…
-
Governing What Agents Cost You
A platform team I spoke with watched their query volume rise 40 times in six weeks. No new dashboards, no new users, no new data sources. What…
-
Semantic View Autopilot for AI Governance
Most data glossaries are wrong by the time you read them. A column gets renamed, a metric changes its grain, a new product line ships, and the human…
-
The State of Agentic AI Standards in 2026: MCP, A2A, WebMCP, OSI, and the Protocol Stack Taking Shape
In 2023, an AI agent was a demo. In 2024, it was a framework. In 2025, it was a hundred incompatible frameworks. And in 2026, something genuinely new…
-
Composable Analytics Beats Metric Catalogs
Metric catalogs tell agents what terms mean. Composable analytics tells agents how to reason with those terms safely. That is the useful lens for…
-
Implementing MCP in the Lakehouse
MCP gives AI clients a standard way to call governed lakehouse tools instead of guessing how to query your data. That is the useful lens for MCP…
-
SaaS Buyers Now Inspect Your Semantic Layer
Enterprise SaaS buyers increasingly want machine-readable data contracts, not only dashboards. That is the useful lens for SaaS semantic layer…
-
Semantic View Autopilot in Snowflake Semantic Studio
Autopilot can draft semantic views quickly, but production semantics still need human review, tests, and governance. That is the useful lens for…