Alex Merced

For the modern analyst, the data experience is too often defined by a spinning wheel and the “ETL tax.” Traditional architectures force a choice: suffer through slow dashboards by querying data in place, or wait weeks for engineering to move data into a proprietary warehouse. This warehouse-first mindset is a relic of the legacy era […]

The most expensive resource isn’t just CPU or storage, it’s time. For the data architect, nothing is more frustrating than watching a multi-terabyte query crawl due to architectural friction. Often, the bottleneck isn’t the data size itself, but the legacy “tax” imposed by how that data is moved, translated, and cached. Dremio is more than […]

Modern data platforms are no longer built around monolithic warehouses or tightly coupled ingestion pipelines. Instead, organizations are standardizing on open lakehouse architectures, where data is stored in open formats, governed by shared catalogs, and processed by multiple engines based on workload. At the center of this shift is Apache Iceberg, which has emerged as […]

The answer to your most critical business question is likely sitting somewhere in your data. The problem? That data is spread across a dozen different systems, from object stores and databases to third-party applications. Getting a straight answer often requires complex ETL pipelines, data copies, and specialized technical skills, creating a frustrating “analytics bottleneck” that […]

Data engineering teams manage growing data volumes, more sources, and tighter delivery timelines. Pipelines break when schemas change. Queries slow as data spreads across systems. Teams spend time tuning performance, fixing failures, and explaining data meaning instead of building value. These problems block analytics and delay AI projects. AI tools for data engineering address these […]

Organizations depend on fast, predictable analytics. Query speed affects dashboards, reports, and automated systems that rely on data every minute. Slow queries increase latency, raise cloud compute costs, and limit how many users a platform can support at once. SQL query optimization sits at the center of this challenge. Teams that design efficient queries reduce […]

The demand for fast, interactive query performance is universal. For decades, the go-to solution for accelerating slow queries has been the materialized view, a pre-computed dataset that stores the results of a query. This approach saves the database from performing expensive joins or aggregations on raw data for every single request. However, traditional materialized views […]

Data chaos is a common challenge. The marketing team uses one business intelligence (BI) tool, finance uses another, and sales has their own set of dashboards. Each team defines “active user” or “monthly revenue” slightly differently, leading to conflicting reports, endless reconciliation meetings, and a pervasive mistrust in the data. The traditional solution to this […]

The success of any AI initiative depends on the data that powers it. Without the right foundation, even the most advanced models will underperform. “AI-ready data” means your information is clean, well-governed, and accessible across teams, enabling accuracy, compliance, and scalability from the start. Key Takeaways Definition: AI-ready data is structured, trusted, and usable, prepared […]

The data lakehouse, supercharged by generative AI, has become the centerpiece of the modern data stack. The promise is alluring: a single, unified platform for all data and analytics, simplified access, and AI that can answer any business question you can articulate in plain English. Yet, many organizations find themselves facing a paradox. The goal […]

For too long, the most valuable information in the enterprise has remained locked away, dormant and inaccessible. I’m talking about the mountains of unstructured data, customer feedback emails, support transcripts, research papers, legal documents, sitting in your data lake. Historically, accessing these insights meant wrestling with complex ETL pipelines, specialized tools, and costly data movement […]

Too often, promising data lakes degrade into data swamps of inefficiency, plagued by slow queries, constant tuning, and complex management. This architectural friction creates data silos and requires specialized teams just to keep the lights on, slowing down the very analytics they were meant to enable. But what if your data lakehouse could manage itself? […]

We collect data from applications, sensors, and customer interactions, storing it across databases, data warehouses, and cloud object storage. Yet, for all this information, getting clear, actionable answers remains the single biggest bottleneck to data-driven decision-making. Answering even a simple business question often requires specialized technical skills, complex SQL queries, and a deep understanding of […]

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 […]