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Dremio Blog: Open Data InsightsData Meaning: Why the Semantic Layer Is the Brain of Agentic Analytics
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Dremio Blog: Open Data InsightsData Unification: The First Pillar of Agentic Analytics
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Dremio Blog: Open Data InsightsWhat Is Agentic Analytics and What Does a True Agentic Analytics Platform Need?
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Dremio Blog: Various InsightsThe Dashboard is Dead
Browse All Blog Articles
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Dremio Blog: Various InsightsYour Data Now Has an AI Assistant: 4 Surprising Ways Dremio Enables Agentic Analytics
These four capabilities are not just a list of features; they are a reinforcing system. The semantic layer provides the context, federation provides the reach, autonomous optimization delivers the speed, and the MCP framework enables the final, crucial step: action. This is the complete blueprint for agentic analytics. -

Dremio Blog: Various InsightsDremio’s latest release delivers AI-Driven Intelligence with the Agentic Lakehouse
Companies are racing to operationalize agentic AI, yet the final process of getting from data to decision is extremely difficult, requiring data integration, tuning, and governance management. With Dremio’s latest release, we remove these blockers by putting natural‑language intelligence, explainability, and self‑optimizing performance directly into the lakehouse experience. You get clarity and control without copies, […] -

Product Insights from the Dremio BlogIntroducing Service Users: Secure Machine-to-Machine Authentication for Dremio
We're excited to announce the introduction of Service Users in Dremio—a new authentication approach designed specifically for the agentic AI era, supporting machine-to-machine (M2M) applications and automated systems. Service users provide a more secure and streamlined way to integrate AI agents, applications, scripts, and CI/CD pipelines with your Dremio environment. What Are Service Users? Service […] -

Product Insights from the Dremio BlogAnnouncing Arrow Database Connectivity (ADBC) in Microsoft Power BI’s Connector for Dremio
We’re excited to share, in partnership with Microsoft, that Dremio is the first agentic lakehouse platform to fully support the open source Apache Arrow Database Connectivity (ADBC) driver for Power BI, bringing next-generation performance to your analytics. Whether you’re working with Dremio Cloud or Dremio Software, this enhancement is available across Power BI Desktop, Power […] -
Dremio Blog: Partnerships UnveiledUsing Dremio, lakeFS & Python for Multimodal Data Management
With lakeFS, you version everything: Iceberg tables, images, models, logs. With Dremio, you query and analyze it all, structured or not, at scale. Together, they bring Git-style control and interactive querying to your data lake, so you can build more intelligent, version-aware workflows without sacrificing flexibility or performance. -
Dremio Blog: Open Data InsightsIngesting Data into Apache Iceberg Using Python Tools with Dremio Catalog
In this blog you will learn how to connect each tool to a REST catalog like Dremio Catalog, using bearer tokens and vended credentials to keep your pipelines secure and portable. -
Dremio Blog: Various InsightsDremio and End-to-End Performance Management
Dremio has introduced several capabilities that inteliigently improve query performance across the data lakehouse. With minimal to no action from users, Dremio will reduce query latency, handle data maintenance tasks, and eliminate redundant compute jobs. This article is a summary of three of these performance management features. Read on to learn how reflections accelerate popular […] -

Dremio Blog: Various InsightsAccelerating AI-Ready Analytics with HPE and Dremio
The Intelligent Lakehouse for the Agentic AI Era Data teams today face a familiar challenge: how to unlock value from ever-growing, scattered data without the delays and cost of traditional ETL pipelines. Together, HPE Alletra Storage MP X10000 and Dremio’s Intelligent Lakehouse Platform solve this problem—combining HPE’s flash-optimized performance with Dremio’s open, unified query and […] -
Dremio Blog: Open Data InsightsUnderstanding Dremio Cloud MCP Servers and How to Use Them
You can move unstructured content into Iceberg tables with AI functions. You can use Dremio’s integrated AI agent for natural language exploration. You can connect external assistants through MCP to build multi-step workflows. All these pieces work together. They give data teams a clear path from raw information to AI-powered insights that stay accurate and trustworthy. -
Product Insights from the Dremio BlogHands-on Introduction to Dremio Cloud Next Gen (Self-Guided Workshop)
Dremio Next Gen Cloud represents a major leap forward in making the data lakehouse experience seamless, powerful, and accessible. Whether you're just beginning your lakehouse journey or modernizing a complex data environment, Dremio gives you the tools to work faster and smarter—with native Apache Iceberg support, AI-powered features, and a fully integrated catalog. From federated queries across diverse sources to autonomous performance tuning, Dremio abstracts away the operational headaches so you can focus on delivering insights. And with built-in AI capabilities, you're not just managing data—you’re unlocking its full potential. -

Product Insights from the Dremio BlogIntroducing Dremio Cloud, The Agentic Lakehouse
We’re excited to announce Dremio Cloud, The Agentic Lakehouse—the lakehouse built for agents and managed by agents. This milestone marks a major leap forward in Dremio’s evolution, reimagining the modern lakehouse for the agentic era, where intelligent systems collaborate with humans to deliver insights, automate operations, and continuously optimize performance. As organizations accelerate their AI […] -
Product Insights from the Dremio BlogIntroducing the VS Code Extension for Dremio
Many data engineers and data analysts spend much of their day in Visual Studio (VS) Code, writing SQL, testing queries, and working with data. Constantly switching between tools disrupts productivity and the user work flow. The VS Code extension for Dremio brings the power of the agentic lakehouse directly into your development environment, enabling you […] -

Product Insights from the Dremio BlogDremio’s Lakehouse AI Agent: From Questions to Actions
Organizations cannot implement AI quickly when data is fragmented across systems, ungoverned, and lacks the business context AI needs to deliver accurate results. Teams juggle schema knowledge, joins, query tuning, visualization tools, and governance checks before they can answer even a simple business question. With Dremio's Agentic Lakehouse—the only data platform built for agents and […] -

Product Insights from the Dremio BlogAI Functions Power Faster Agentic Analytics and Insights
The rapid growth of the use of AI throughout the modern data stack has transformed how organizations extract insights from their data. With our latest release, we're excited to announce the general availability of AI Functions — a capability that brings the power of Large Language Models (LLMs) directly into SQL execution, making Dremio’s Agentic […] -

Product Insights from the Dremio BlogGet Enhanced MCP Server Data Exploration with Dremio’s Agentic Lakehouse
Discover how Dremio’s Next Generation Cloud and enterprise MCP Server simplify data exploration with AI-driven queries, governance, and natural-language SQL.
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