For years, organizations have invested in data platforms to understand what happened across their business. Dashboards, reports, and KPIs are now table stakes. But as AI becomes central to how organizations operate, the bar for the data lakehouse is getting much higher.
The next generation of applications and agents needs governed access to every kind of data: structured, semi-structured, and unstructured; batch, streaming, and real-time—working together on one open foundation. When that data remains spread across fragmented systems, teams are left reconciling copies, duplicating governance, and stitching together context before they can create value.
Today, we're proud to share that Microsoft has been recognized as a Leader in The Forrester Wave™: Data Lakehouses, Q3 2026. In the report, Forrester describes Microsoft Fabric as “a strong fit for enterprises seeking a unified, AI-enabled lakehouse platform integrated with the Microsoft ecosystem.”
We believe this recognition reflects the bold vision behind Microsoft Fabric and Microsoft OneLake: helping organizations eliminate the integration tax of fragmented data estates by bringing data, analytics, governance, and AI together on one open lakehouse foundation.
Fabric: A unified foundation for the AI-era lakehouse
The Forrester report frames the modern lakehouse as more than a system of record for analytics. As agentic AI systems begin to reason, plan, and act on enterprise data, the lakehouse is becoming the operational foundation where intelligence is grounded and activated in real time.
Microsoft Fabric was built for this shift. With OneLake, Fabric gives organizations a single, governed data lake and one SaaS platform where data teams, analysts, developers, and business users can work from the same trusted foundation. Forrester notes that Microsoft’s approach emphasizes deep integration across Power BI, Copilot, Microsoft 365, OneLake, databases, and AI services—helping unify analytics, operational, and AI workloads within a single ecosystem.
Forrester also highlights Microsoft’s “bold vision of a unified, AI-powered, open data platform that brings together analytics, data engineering, business intelligence, and operational data.” Furthermore, they add that “innovations such as OneLake shortcuts, mirroring, AI-powered transformations, and cross-cloud interoperability support this vision by reducing silos and simplifying access to distributed data.”
One open foundation for data and analytics
OneLake is the governed data lake at the heart of Fabric, designed to unify your entire multi‑cloud data estate. It connects data across clouds and on‑premises systems using zero‑copy, zero‑ETL access, so teams work from a single, governed copy of data. With native support for open formats like Delta Lake and Iceberg, this data remains accessible from any analytics engine or platform, including Microsoft Fabric, Snowflake, and Azure Databricks. Once data is connected or stored in OneLake, the OneLake catalog helps secure, govern, and organize it into a logical data mesh, making trusted data easy for everyone to discover and use.
Govern once, across every engine
Security, identity, lineage, and governance are built into Fabric rather than bolted on tool by tool. State of the art OneLake security can define object-, row-, and column-level controls once and enforce them consistently across Spark, SQL, KQL, Power BI, Copilot, and third-party engines through OneLake security APIs. The OneLake catalog centralizes sensitivity labels, classification, and end-to-end lineage, helping organizations simplify governance while giving users trusted access to the data they need.
Every workload on one lakehouse
Fabric brings relational, real-time, analytical, document, and vector workloads into one platform experience on OneLake. Spark powers data engineering with the Native Spark Execution Engine in Microsoft Fabric, which accelerates workloads by running much of the execution in highly optimized native C++ code with vectorized processing, while preserving the same Spark APIs, notebooks, and DataFrame code users already know. With the native execution engine, Spark in Fabric delivers up to 6x faster performance than open-source Apache Spark, helping improve price performance by completing the same workloads with less compute and lower costs.
Additionally, the warehouse engine and lakehouse SQL endpoint serve interactive queries over the same Delta tables; Real-Time Intelligence supports streaming and event-driven scenarios; and Power BI queries OneLake directly through Direct Lake without importing or moving data.
AI native to the data platform
Fabric’s integration with Copilot and agents enable natural language analytics and intelligent automation at scale. Vector embeddings can sit alongside structured data for AI retrieval, so teams can build analytics, AI, and applications on one governed copy of data. Instead of moving data to each workload, organizations can bring more workloads and more AI-powered experiences to the same open lakehouse.
Why organizations choose Fabric
Customers are seeing real impact from using Fabric: less duplication, cleaner governance, faster development, and a simpler path from data to AI.
At the foundation is a common pattern: organizations are consolidating fragmented data estates onto a single governed lakehouse. London Stock Exchange Group (LSEG), a partner to the world's leading financial institutions, set out to simplify a complex, fragmented data landscape and give its customers a consistent, unified experience. Using Fabric, LSEG is building a unified data platform that consolidated 30 systems, 1,200 datasets, and 33 petabytes of data, accelerating product development, improving data quality, and advancing AI readiness. Product development timelines have moved from years to months, delivering faster, cleaner data to everyone from global firms to individual traders.
"When you need to pull data together across disparate sources that are in different formats and varying levels of modernisation and maturity, it makes it difficult to react to market demand quickly. We knew it would be far more efficient to bring everything into a single, modern platform. It would mean we could run the organisation leaner and react to market demand faster.”
- Dave Byrne, Group Head of Data Platforms at LSEG
Once data is unified, organizations can apply governance and analytics at enterprise scale. UNC Health standardized its enterprise data estate on Fabric, creating a single, governed lakehouse foundation for clinical analytics, operations, population health, and research. Fabric powers UNC Health’s AI solutions, which reduced care-gap chart review time by nearly 50% and provides the governed data foundation for a secure research environment supporting 25 active studies.
That same foundation also creates new opportunities for AI-driven innovation. Eastman, a global specialty materials company, adopted Fabric to modernize its legacy data architecture and create a unified, governed lakehouse foundation for analytics and AI. Using OneLake shortcuts and data mirroring, Eastman shares data across domains without unnecessary duplication, ingested roughly one billion rows from eight systems, and established a scalable platform for analytics, machine learning, and AI-powered applications.
“We operate in a lot of markets that are fundamentally different from one another. Being able to aggregate all this loose, unstructured data into something that’s actionable is really helping our commercial organization build better strategies for the year ahead.”
—Andrew Ervin, Manager of Generative AI, Eastman
Taken together, these examples illustrate the evolution of the modern lakehouse: first unifying data, then governing it consistently, and ultimately turning it into a foundation for AI-powered innovation. This is the shift that many organizations are making as they prepare for the next generation of applications and agents.
Strategic takeaways for enterprise leaders
Three shifts stand out for leaders preparing their organizations for the next generation of AI:
The lakehouse is now the default foundation for AI. Agents and AI applications need governed access across every data type; not siloed systems stitched together after the fact.
Openness prevents lock-in. Open table formats and bi-directional interoperability help organizations unify their estate without walking away from the tools and platforms they already run.
Reducing duplication changes the economics. Bringing workloads to a shared, governed foundation helps organizations simplify operations, strengthen consistency, and accelerate innovation.
As organizations prepare for the next generation of AI-powered applications and agents, the need for a unified, open, and governed data foundation will only grow. Microsoft Fabric was built to bring data, analytics, governance, and AI together on that foundation, and we’re excited to keep innovating alongside our customers.
Forrester’s recognition reinforces what we’ve believed from the start: the organizations that succeed in the AI era will be those that eliminate fragmentation, simplify governance, and build on one open lakehouse.
Learn more
- Read the complimentary report.
- Explore Microsoft OneLake and Microsoft’s vision of an open data lake ecosystem.
- Join us at the next Fabric + SQL Community Conference in Barcelona to hear directly from our product and teams and community members.
Statement from Forrester
Forrester does not endorse any company, product, brand, or service included in its research publications and does not advise any person to select the products or services of any company or brand based on the ratings included in such publications. Information is based on the best available resources. Opinions reflect judgment at the time and are subject to change. This report is part of a broader collection of Forrester resources, including interactive models, frameworks, tools, data, and access to analyst guidance. For more information, read about Forrester's objectivity here.