The Dremio Blog

The Energy and Utilities industry faces some of the most demanding regulatory and operational pressures in the world. From NERC CIP requirements in the power grid, to TSA directives in pipelines, to the EU’s NIS2 obligations, the stakes are high: protect sensitive data, demonstrate compliance, and maintain uninterrupted service to millions of customers.

For financial and insurance companies, compliance is not just a legal requirement, it’s a strategic imperative. The overlapping patchwork of regulations, from NAIC Model Laws and HIPAA to Basel III, MiFID II, GDPR, and PCI DSS, makes it clear that data governance and security must be woven into the very fabric of an organization’s data strategy. At the same time, customers expect real-time experiences, transparent policies, and the assurance that their most sensitive information is being handled with care.

Healthcare organizations face a unique challenge: they must manage some of the world’s most sensitive data while also unlocking its potential to improve patient outcomes, accelerate research, and streamline operations. Regulations like HIPAA, HITECH, GDPR, and the 21st Century Cures Act ensure accountability, but they also raise the bar for data security, governance, and interoperability.

AI without governance is a liability. Governance without speed is a bottleneck. Dremio’s semantic layer eliminates this trade-off by providing governance without friction. With a single, governed interface exposed to AI agents via the MCP server, organizations can unlock AI-powered analytics that are fast, secure, and business-friendly.

In the AI era, speed is the differentiator. Dremio’s autonomous reflections make it possible to achieve sub-second responses without endless tuning or fragile performance layers.

The future of AI-driven analytics isn’t about choosing between SQL and semantics, it’s about combining them. Dremio’s MCP server provides the best of both worlds, enabling agents to query, discover, and interpret enterprise data with confidence.

AI will only be as good as the data foundation it stands on. With Dremio’s AI-enabled semantic layer, organizations can unlock the promise of agentic analytics while maintaining governance, consistency, and performance.

The future of analytics isn’t about replacing people with AI, it’s about augmenting decision-making with intelligent, governed access to data. Dremio’s MCP server opens the lakehouse to this new generation of agents, ensuring that insights are not only fast but also accurate, secure, and aligned with business definitions.

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 […]

Apache Iceberg 1.10.0 represents a turning point in the evolution of the open lakehouse. With the general availability of format-version 3, Iceberg now offers a more complete solution for organizations seeking the flexibility of data lakes combined with the reliability of data warehouses. Features like binary deletion vectors, default column values, and row-level lineage aren’t just incremental improvements, they redefine what’s possible in managing massive, ever-changing datasets.

By standardizing the interaction between hosts, clients, and servers, MCP unlocks true modularity. You can swap models without breaking workflows, mix and match servers for analytics, email, or storage, and grow your AI capabilities incrementally. The Dremio + SendGrid example shows how easily analytics and action can come together, transforming what used to be manual, multi-step processes into fully automated workflows.

For organizations exploring agentic AI, this translates into a critical edge: AI agents can generate dynamic, ad-hoc questions and still receive sub-second, business-ready answers. With reflections, the performance layer is no longer a bottleneck, it becomes an enabler of intelligent, real-time decision-making.

Dremio’s MCP server, integrated semantic layer and autonomous reflections deliver this combination. They turn natural‑language intent into secure, performant and semantically rich analytics, enabling agents to act not just as chatbots but as trustworthy decision‑makers.

The direction is clear: the open lakehouse is no longer about choosing between flexibility and performance, or between innovation and governance. With Arrow, Iceberg, and Polaris maturing side by side, and with Dremio leading the charge, the open lakehouse has become a complete, standards-driven foundation for modern analytics. For enterprises seeking both freedom and power, this is the moment to embrace it.

Apache Iceberg closed that gap by transforming collections of Parquet files into true tables, complete with ACID transactions, schema flexibility, and time travel capabilities. And with Apache Polaris sitting on top as a catalog, organizations finally have a way to manage all those Iceberg tables consistently, delivering centralized access, discovery, and governance across every tool in the stack.