2026-07-28 • Alex Merced
Guardrails for Analytics Agents That Do More Than Answer Questions
The risk isn't agents going rogue, it's agents acting correctly on bad input at machine speed. Here's how to classify ac...
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Data Lakehouses & Agentic Analytics
Authoritative guides to the modern data ecosystem — curated from Dremio's engineering blog.
Semantic Layer
The Semantic Layer: Definitive Guide
A comprehensive guide to the Semantic Layer — how it creates a single source of truth for metrics, powers headless BI, and makes AI agents answer business questions accurately.
Read on Dremio.com →Apache PolarisApache Polaris: The Catalog Standard for Lakehouses and AI
How Apache Polaris is emerging as the universal Iceberg catalog standard, enabling multi-engine interoperability and governed AI access across the lakehouse ecosystem.
Read on Dremio.com →Table FormatsWhat Are Table Formats and Why Were They Needed?
The origin story of open table formats — the problems with Hive, why Apache Iceberg, Delta Lake, and Hudi were created, and what they unlock for modern data platforms.
Read on Dremio.com →DremioWhat Is Dremio?
A clear-eyed breakdown of what Dremio is, how its semantic layer, query federation, Reflections, and Apache Arrow Flight power the Intelligent Lakehouse Platform.
Read on Dremio.com →Apache IcebergWhat Apache Iceberg Native Actually Means
Not all 'Iceberg support' is equal. This piece breaks down what it means to be genuinely Apache Iceberg native versus bolt-on, and why it matters for your lakehouse.
Read on Dremio.com →Open SourceOpen Source and the Data Lakehouse
How the Apache Software Foundation's open-source projects — Iceberg, Arrow, Parquet, Polaris — form the modular foundation of the modern open data lakehouse.
Read on Dremio.com →Agentic AIWhat Is Agentic Analytics?
Agentic AI is reshaping how organizations interact with data. This guide explains agentic analytics, the role of the semantic layer, and why query performance matters for AI agents.
Read on Dremio.com →Data LakehouseDefinitive Guide to the Data Lakehouse
The complete, authoritative guide to the Data Lakehouse architecture — what it is, why it supersedes the data warehouse + data lake combination, and how to build one.
Read on Dremio.com →AI & PerformanceHow Dremio Keeps Agentic Analytics Fast Without Manual Tuning
How Dremio's layered autonomous performance architecture — Reflections, caching, vectorized execution — handles unpredictable AI agent query patterns at interactive speed.
Read on Dremio.com →Recent Articles
Latest from IngestThis
Data Engineering, Data Architecture, and AI insights fresh from our writers.
2026-07-28 • Alex Merced
Building Agent Telemetry Tables in Iceberg That Survive an Audit
A practical guide to building agent decision traces in Apache Iceberg that support audit reconstruction, governance revi...
2026-07-28 • Alex Merced
What Agentic Analytics Actually Costs, and How to Keep It Bounded
Agent analytics generates two cost streams that scale on different variables. Here's the arithmetic, the levers that act...
2026-07-28 • Alex Merced
Running an Apache Iceberg Lakehouse With No Internet Connection
A practical guide to deploying an Iceberg lakehouse in air-gapped environments: component choices, artifact pipelines, i...
2026-07-28 • Alex Merced
When the Query Optimizer Starts Managing Its Own Materializations
Autonomous materialized view management replaces quarterly review meetings with workload-driven scoring, and it's essent...
2026-07-28 • Alex Merced
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 th...