Explores Dremio's automated materialized views and reflections for optimizing AI-era lakehouse workloads beyond static cron-based maintenance.
Analysis of Dremio's Lakehouse AI report on shifting enterprise priorities from cost migration to agent-ready data platforms.
Explores moving from passive BI dashboards to closed-loop decision agents that observe, reason, validate, and act on data within a lakehouse architecture.
Explores fine-grained security for AI agents in analytics, covering dynamic access control, identity propagation, and governance at machine speed.
Explores the Dremio Agentic Lakehouse concept: data built for AI agents and platform management automated by agents, with architecture patterns and production considerations.
Overview of AI agent tooling from major data platforms in 2026, focusing on MCP integration and native capabilities.
Tutorial on building a custom agentic analytics system using Python, LangChain, and Dremio SQL data lakes for automated SQL investigation.
Explains designing an open catalog architecture for AI agents in an agentic lakehouse, covering Apache Polaris and Dremio's Open Catalog.
Explains how semantic layers improve enterprise Text-to-SQL accuracy from 40% to 85-95% by providing structured context for AI.
A practical walkthrough of working with Apache Iceberg on Dremio Cloud, covering table creation, data ingestion, optimization, and AI-powered analytics.
A guide to integrating Dremio's data lakehouse platform with Amazon Kiro's AI IDE for data querying, app building, and pipeline generation.
A guide to connecting Dremio's data lakehouse platform with Claude Code, enabling the AI coding agent to query live data and build data applications.
A guide to integrating Dremio's data lakehouse platform with Claude CoWork, enabling natural language queries, automated reporting, and data app development.
A guide to integrating Google's Gemini CLI with Dremio's data platform for querying, building data apps, and generating SQL using AI.
A guide on integrating Dremio's data platform with the Cursor AI code editor to enable accurate SQL generation and data app development.
A guide to integrating GitHub Copilot with Dremio's data platform to enable AI-assisted SQL generation, data pipeline creation, and application development.
A guide to integrating Google Antigravity AI agents with the Dremio lakehouse platform for enhanced data querying and application development.
A guide to integrating Dremio's data platform with JetBrains AI Assistant for enhanced data querying, pipeline generation, and app development within JetBrains IDEs.
Guide on integrating Dremio data lakehouse with OpenAI Codex CLI for querying, building data apps, and generating analytics code.
A guide to integrating the Dremio lakehouse platform with the OpenCode AI coding agent for data querying and application development.
