Microsoft boosts Fabric to make it a foundation for AI
New features that feed agents contextually relevant data add breadth to the platform and keep its data and AI capabilities current in a competitive market.
Microsoft is making Fabric a foundation for agentic AI.
First launched in 2023, Fabric brought together seven previously disparate Microsoft data management and analytics capabilities, such as Data Factory and Power BI, and infused them with generative AI through early iterations of its Copilots.
As enterprises have increased their investments in developing agents and other AI applications, additions such as OneLake to unify data and Model Context Protocol servers to connect agents with data sources marked Fabric's evolution toward becoming a base for developing agents that can understand the unique characteristics of an individual business.
Microsoft's latest Fabric capabilities, unveiled on Tuesday during its Build user conference in San Francisco, are designed to further aid developers attempting to create AI tools that can be trusted to perform properly in production. Among them are a tool that unifies business logic to form a contextual foundation for agents and a database purpose-built for the scale of AI workloads.
Collectively, the new Fabric features are valuable to Microsoft users because they directly address problems enterprises face when attempting to move agents beyond pilots and into production, according to William McKnight, president of McKnight Consulting.
"Microsoft is introducing a suite of features designed to eliminate the context bottleneck by providing AI agents with a persistent, shared understanding of business data," he said. "Key updates … merge application backends, high-speed processing and semantic context into a platform capable of deploying autonomous, enterprise-scale AI agents -- the goal of many organizations today."
Mike Leone, an analyst at Moor Insights & Strategy, similarly noted the significance of Microsoft's new Fabric features, particularly those that the tech giant terms ontology capabilities that help agents understand what an enterprise's data means in the context of its business.
"The real story is that Microsoft is closing the distance between where your data lives and where agents actually act on it," he said. "What stands out is that you can … give agents a clear map of what that data means in your business and then let them act on it directly. That round trip, from raw data to an app or agent that does the work, used to take stitching three or four separate systems together."
Grounding for AI
Many enterprises are making a push to move past experiments with AI to put agents into production. However, disorganized data that makes it difficult to discover and operationalize the contextually relevant data agents require to deliver accurate outputs remains an obstacle for many.
Microsoft is introducing a suite of features designed to eliminate the context bottleneck by providing AI agents with a persistent, shared understanding of business data.
William McKnightPresident, McKnight Consulting
Like numerous other data management and analytics providers -- Databricks, Google Cloud and Snowflake among them -- Microsoft is now making context for AI a focal point of its product development plans for Fabric.
"Context matters because as models become more capable and more available, the differentiator isn't just access to intelligence, it's the ownership," Kyle Daigle, Microsoft's developer chief marketing officer, said during a virtual press briefing before Build. "The real question every organization is asking is how to use your expertise, your data, and your way of working."
New features unveiled during Build include the following:
Microsoft IQ, an enterprise intelligence layer for AI that unifies an organization's data estate and joins it with semantic meaning and business logic to empower agents.
Fabric IQ, a feature within Microsoft IQ that grounds AI with consistent definitions, metrics and relationships.
Rayfin, a backend-as-a-service feature for application development that runs on top of Fabric.
New shortcuts in OneLake that make it easier to connect data across platforms so users don't have to move or duplicate data.
GPU-accelerated workflows in Fabric Data Warehouse to improve query performance.
A database hub in Fabric where customers can centrally manage their Microsoft databases.
Azure HorizonDB, a new PostgreSQL database in public preview that improves on the performance and scalability of Azure Database for PostgreSQL to better handle AI workloads.
New security capabilities in preview for existing workloads in Azure Database for PostgreSQL.
The general availability of Azure Cosmos DB Linux Emulator, a tool that enables users of Microsoft's NoSQL vector database to locally build, test and validate applications across Linux, macOS and Windows without having to do their work in a cloud environment.
Capabilities in Fabric IQ that allow customers to define their data once and have that definition used by every agent provided by Microsoft are among the most valuable, according to Leone.
"Instead of re-teaching each new agent what a customer or an order is in your business, you set it once and they all inherit it, and that kind of reuse is hard to pull off unless you own both the data layer and the agent tooling, which few players do," he said.
As Microsoft adds capabilities to Fabric, the platform is evolving to become a well-designed bridge for moving AI experiments into production, Leone continued. However, he noted that better data governance guardrails, an orchestration framework for multi-agent networks and operationalization of unstructured data could all improve Fabric.
Meanwhile, from a competitive standpoint, Microsoft differentiates itself with the breadth of its data and AI capabilities, though individual tools are perhaps not as deep as those provided by more specialized vendors, according to Leone.
"I'd put Microsoft right at the front of the pack on the unified data foundation idea, and the differentiation is breadth," he said. "Pulling analytics, transactional databases, a semantic layer, and now app development into one platform is a more integrated bet than most of the specialized data platforms are making, since those players tend to go deeper in their lane while Microsoft goes wider."
"Fabric IQ and Rayfin serve as the core pillars for building enterprise-grade AI, respectively solving the critical challenges of data context and deployment speed," McKnight said. "Fabric IQ eliminates the context bottleneck [and] Rayfin then operationalizes this intelligence. … Together, they allow developers to transition their experiments to production-ready multi-agent systems."
Comparatively, Microsoft's data and AI capabilities are in line with those of its hyperscale cloud competitors, he continued.
"Microsoft's AI data strategy -- Fabric, OneLake, Purview and integrated vector stores -- positions it securely alongside the hyperscaler cohort, excelling in platform integration while playing catch-up in technical depth compared to specialized vendors. It excels in bundling, operational simplicity, and ecosystem coherence rather than inventing net-new data primitives."
Looking ahead
As Microsoft continues to build up Fabric as a foundational layer within its data and AI platform, there remains room for improvement, according to McKnight. While its overall capabilities are competitive, specific areas such as governance, interoperability with third-party platforms, workflow depth and cost transparency all need addressing.
Specifically, McKnight suggested that Microsoft make Purview -- an integrated security, governance and compliance service -- more AI-ready, embrace open table formats and add built-in LLMOps and agentic orchestration capabilities.
"This would help position Fabric as the definitive, safe choice for production-grade AI," he said.
Leone, meanwhile, advised Microsoft to make it easier for new customers to get started with Fabric so it evolves from a default platform for existing customers to a destination for new ones.
"First, make it dead simple to start small, because most new customers aren't moving their whole data estate on day one," he said. "Let them adopt one workload, … and expand from there instead of feeling like they have to buy into the entire platform up front. Second, the faster and lower-risk it makes moving, the more Fabric turns from a Microsoft-shop default into a real destination for brand-new customers."
Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than three decades of experience. He covers analytics and data management.
