Tag: semantic layer
All the articles with the tag "semantic layer".
- 21 MIN READ•Aug 4, 2026
Why Agentic AI Needs a Governed Semantic Layer Behind the Model Context Protocol
Why agentic AI needs a governed semantic layer behind the Model Context Protocol: metric consistency, access control, Apache Ossie for portable definitions, and Apache Polaris for enforcement.
AI AgentsMCPSemantic Layer - 21 MIN READ•Aug 4, 2026
Metric Contracts as the Interface AI Agents Actually Need
Metric contracts as the interface AI agents need: calculation, inclusion rules, grain, temporal semantics, ownership, semantic versioning, and testing metrics in CI.
AI AgentsMetric ContractsSemantic Layer - 31 MIN READ•Jul 28, 2026
Why AI Agents Fail on Raw Data, and What to Give Them Instead
Agents fail on raw lake data because business rules live in people's heads. Data products with semantic contracts fix this at the source.
AI AgentsApache IcebergSemantic Layer - 31 MIN READ•Jul 28, 2026
The Five Layers Between Your Lakehouse and a Trustworthy Agent
Agent reliability is a property of the stack the model sits on. Five layers with distinct owners and failure modes turn the agent is unreliable into a specific diagnosis.
AI AgentsApache IcebergData Architecture - 31 MIN READ•Jul 25, 2026
Governing What Agents Cost You
Agents break the four assumptions analytics platforms were built on. A practical guide to identity, budgets, semantic layers, caching, and instrumentation for agent workloads.
AI agentscost governancedata platform - 17 MIN READ•Jul 13, 2026
Semantic View Autopilot for AI Governance
An in-depth exploration of semantic view autopilot for ai governance
Semantic LayerGovernanceAI Agents - 29 MIN READ•Jul 6, 2026
The State of Agentic AI Standards in 2026: MCP, A2A, WebMCP, OSI, and the Protocol Stack Taking Shape
The agentic AI protocol stack is solidifying in 2026 — MCP for tools, A2A for agents, WebMCP for the web, OSI for semantics, payments, identity, and security.
Apache Icebergdata engineeringlakehouse architecture - 14 MIN READ•Jun 22, 2026
The Model Is Not the Moat
Enterprise AI advantage increasingly comes from governed context, semantic models, and operational data contracts, not only from model choice.
enterprise AI moatsemantic layergoverned lakehouse AI - 15 MIN READ•Jun 8, 2026
Composable Analytics Beats Metric Catalogs
Metric catalogs tell agents what terms mean. Composable analytics tells agents how to reason with those terms safely.
semantic layerdata governancecomposable analytics - 15 MIN READ•Jun 8, 2026
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.
lakehousesemantic layerdata governance - 15 MIN READ•Jun 8, 2026
SaaS Buyers Now Inspect Your Semantic Layer
Enterprise SaaS buyers increasingly want machine-readable data contracts, not only dashboards.
semantic layerdata governanceSaaS procurement - 14 MIN READ•Jun 8, 2026
Semantic View Autopilot in Snowflake Semantic Studio
Autopilot can draft semantic views quickly, but production semantics still need human review, tests, and governance.
Snowflakesemantic layerdata governance