Alex Merced

Multimodal data, ranging from images and logs to structured tables, powers today’s AI systems, but managing these diverse assets in sync remains a significant challenge. While software teams benefit from Git workflows to track code versions, data teams often lack equivalent tools to version, isolate, and merge changes across multiple data types. That’s where lakeFS […]

Get your free Dremio Catalog by signing up for the Dremio Cloud Free Trial Self-guide workshop on using Dremio’s Features During Free Trial Previous Article I wrote around tools for ingesting into Apache Iceberg Ingesting Data into Apache Iceberg with Dremio Apache Iceberg gives teams a simple way to manage data in a lakehouse. It […]

Artificial intelligence is moving fast, but every model still faces the same limitation: it cannot deliver reliable answers without access to reliable data. For an AI agent to make good decisions, it needs direct access to live, governed information and the business context that comes from a well-structured data platform. Dremio Cloud solves this problem […]

Video Playlist of this Walkthough On November 13, at the Subsurface Lakehouse Conference in New York City, Dremio announced and released Dremio Next Gen Cloud, the most complete and accessible version of its Lakehouse Platform to date. This release advances Dremio’s mission to make data lakehouses easy, fast, and affordable for organizations of any size. This tutorial offers […]

Building AI solutions isn’t just about algorithms, it’s about the data that powers them. For AI models to be accurate, reliable, and safe, enterprises must modernize how they collect, store, govern, and serve data. This requires data architectures that support openness, scale, and governance from the ground up. This blog walks through the tools, techniques, […]

AI-ready data is structured, governed, and accessible in a way that supports machine learning, large language models (LLMs), and real-time intelligent agents. Unlike traditional analytics data, it’s not just clean, it’s optimized for rapid, automated decision-making at scale. AI-ready data supports diverse formats, is accessible without ETL, and maintains the context required to train and […]

Apache Polaris is quickly becoming the standard open catalog for Iceberg lakehouses. Version 1.2.0 brings more control, better compatibility, and early steps toward deeper observability. If you’re building a lakehouse that supports multiple tools or engines, Polaris helps keep everything consistent, governed, and performant. This release focuses on practical improvements. Teams now have more precise […]

File formats rarely get the spotlight. They sit under layers of query engines, orchestration tools, and machine learning frameworks, quietly doing the heavy lifting. Yet, the way we store and access data has a direct impact on everything from query latency to model accuracy. And right now, the file format space is undergoing one of […]

Apache Polaris brings open, standards-based governance to the modern data lakehouse. It provides a central catalog that defines how Iceberg tables are organized, accessed, and secured across engines and clouds. For anyone who wants to understand how Polaris works, running it locally is the fastest way to see its features in action. This guide walks […]

The data world is moving fast. AI agents are no longer science fiction; they’re showing up in workflows, automating tasks, generating insights, and acting on behalf of users. But for these agents to be effective, they need more than just good models. They need consistent, fast, and governed access to enterprise data. That’s where Dremio’s […]

Apache Iceberg provides a powerful foundation for managing large analytical datasets, but like any data system, performance depends heavily on how well the data is organized on disk. Over time, frequent writes, schema evolution, and streaming ingestion can leave tables fragmented with many small files or oversized files that hurt query speed. Left unmanaged, this […]

Managing Apache Iceberg tables effectively is often a balancing act between write performance, storage efficiency, and query speed. While Iceberg’s flexibility enables powerful features like time travel and schema evolution, many teams find themselves running frequent OPTIMIZE jobs to compact small files and rebalance partitions. These jobs improve performance but also consume valuable compute resources, […]

Apache Iceberg’s snapshot-based architecture is one of its greatest strengths, enabling time travel queries, rollbacks, and strong auditability. But with every update, new snapshots are created and old data files linger. Over time, this leads to growing storage costs, expanding metadata, and, perhaps most importantly, questions around regulatory compliance. How do you ensure that data […]

The emergence of agentic AI, intelligent systems that can reason, plan, and act through connected tools, has fundamentally changed how engineers and organizations think about integrating data into intelligent workflows. These agents aren’t limited to answering questions. They can coordinate tasks, trigger business actions, and collaborate with other agents to execute complex processes. Yet one […]

From farm to fork, today’s food supply chains generate enormous volumes of data. Every shipment, every temperature check, every sustainability report leaves behind a digital trail, and regulators in both the EU and the U.S. now expect that trail to be complete, accurate, and instantly accessible. Rules like the FDA’s Food Safety Modernization Act (FSMA) […]

Data has become the backbone of decision-making for the education industry. From student performance metrics to administrative records and learning management systems, institutions are generating and managing more information than ever before. But with this growth comes heightened responsibility. Strict regulations like FERPA in the U.S., GDPR in Europe, COPPA for children’s online privacy, and […]

Modern transportation and automotive companies are awash in data. A single connected car can generate up to 25 GB of data every hour as its sensors, telematics units and infotainment systems stream information about vehicle health, location, driver behaviour and passenger preferences. This torrent of data has become a competitive advantage: manufacturers and fleet operators use […]

Telecommunications companies sit at the center of the world’s digital connectivity, powering everything from mobile networks to internet services. But with this responsibility comes a unique challenge: telecom providers handle some of the most sensitive forms of customer information, including call records, location data, and usage patterns. A single breach of this trust doesn’t just […]

The Energy and Utilities industry sits at the intersection of two worlds: critical infrastructure and rapid digital transformation. Power grids, pipelines, and water systems increasingly rely on data-driven operations, from real-time monitoring of SCADA systems to predictive maintenance powered by machine learning. But with this opportunity comes immense responsibility. Strict regulations, such as NERC CIP […]

In the finance and insurance industries, data is both an asset and a liability. Every transaction, policy, claim, and customer record carries not only business value but also heavy regulatory obligations. Institutions operate under a web of global, federal, and state rules, from GDPR, CCPA, and PCI DSS to industry-specific mandates like Dodd-Frank, SOX, NAIC […]

Healthcare data is among the most sensitive information any organization manages. Electronic health records, lab results, insurance details, and billing data all contain protected health information (PHI) that, if exposed, could cause immense harm to patients and carry heavy regulatory penalties for providers. This is why laws like HIPAA, HITECH, and the 21st Century Cures […]

AI agents thrive on data, but without governance, they risk delivering insights that are inconsistent, misleading, or even non-compliant. Enterprises cannot afford to let AI run wild across their data landscape. The challenge is clear: how can organizations give AI agents the access they need without losing control? Dremio’s semantic layer provides the answer. It […]

When people interact with AI copilots or conversational agents, expectations are high. We want answers that are not only accurate but also instantaneous. In the enterprise world, this means your data platform must deliver sub-second query responses, even on massive datasets. This is where Dremio’s autonomous reflections play a critical role. By combining performance optimization […]

AI agents are only as effective as the data interfaces they can use. For decades, SQL has been the universal language for querying data. But in the age of AI and autonomous analytics, SQL alone isn’t enough. Agents need governed, context-rich access to data, and that’s exactly what Dremio’s MCP server delivers. By combining SQL […]

AI agents and copilots promise to revolutionize how we interact with data. But while they can generate answers quickly, the real question is: are those answers accurate, consistent, and trustworthy? This is where Dremio’s AI-enabled semantic layer comes into play. It provides the foundation for business-friendly analytics by combining powerful semantic search with governance and […]

As AI agents are adopted to streamline operations, a central challenge arises: how can these agents access enterprise data securely, accurately, and in a way that reflects business context? Dremio’s open-source MCP server delivers exactly that, bridging the gap between large language models (LLMs), AI agents, and governed data in the lakehouse. Exposing the Lakehouse […]

Every year, the Gartner® Hype Cycle™ for Data Management helps us understand which technologies are generating buzz and which are delivering real business impact. In the 2024 report, one placement caught my attention: the data lakehouse has shifted from the Peak of Inflated Expectations into the Trough of Disillusionment. At first glance, this might sound […]

The Apache Iceberg project has steadily evolved into the backbone of modern open data lakehouses, delivering performance, reliability, and interoperability across a wide range of engines. With the release of Apache Iceberg 1.10.0, the community takes a major step forward by bringing the long-anticipated format-version 3 (V3) features into general availability. This release isn’t just […]

Artificial Intelligence is moving beyond static chatbots and single-model applications into a new era of agentic AI, systems that can reason, plan, and act by coordinating with multiple tools and data sources. At the heart of this shift is the Model Context Protocol (MCP), a new open standard designed to make connecting AI systems to […]

Traditional business intelligence relied on static dashboards and predictable queries, where materialized views and cubes could be tuned once and used repeatedly. But the rise of agentic AI has upended that model. Instead of fixed reports, AI agents generate ad-hoc, ever-changing questions that demand instant, accurate answers from massive datasets. Meeting these requirements with yesterday’s […]