The excitement in Barcelona mirrors the momentum we’re seeing throughout Microsoft’s data portfolio. Microsoft Fabric now supports more than 40,000 customers worldwide, and for decades Microsoft SQL Server has provided the backbone of enterprise workloads including more than 90% of the Fortune 500. Customers like Levi Strauss, Australian Energy Market Operator, and University of North Carolina Health are using these capabilities to unify their data estates, ground AI in their business context, and scale while remaining governed and secure.

Today, we’re announcing new innovations across Microsoft Fabric and our database portfolio designed to help organizations power their Frontier Transformation, including deep integrations with the new Microsoft Copilot, agentic app development in Microsoft Power BI, end-to-end observability in Fabric, the database hub, and more.

Power your AI transformation with Microsoft Fabric

Enabling Frontier Transformation with Microsoft Copilot and Microsoft Fabric

Software development has changed dramatically. AI is no longer simply helping developers write code faster. Agents are beginning to work across the full development lifecycle, from planning and coding to testing and deployment.

The opportunity now is to bring that same transformation to the rest of the enterprise. But organizations need more than models and agents. They need trusted context: governed data, shared business definitions, operational knowledge, and the guardrails that help AI act reliably.

This is the foundation of Frontier Transformation: embedding AI into core business processes, grounded in an organization’s unique data, knowledge, and workflows. Microsoft is helping enable this transformation through Microsoft Copilot and Microsoft IQ, which connect AI to an organization’s knowledge, data, applications, and business context.

At the center of this system is Fabric IQ, a shared intelligence layer that connects enterprise data, business metrics, and operational context across the Microsoft ecosystem. By combining unified data from Microsoft OneLake, trusted metrics from Power BI semantic models, and operational context from ontologies and real-time intelligence, Fabric IQ gives people and agents a shared understanding of the business.

Powering the new Microsoft Copilot with trusted data from Fabric IQ

Millions of Microsoft 365 users rely on Microsoft Copilot every day to find information, create content, analyze data, and take action in the flow of work. With the introduction of the new Copilot last week, it’s evolving from a conversational assistant into a unified experience where people can assist, delegate, and even build. Home brings Chat and Cowork together, while Code now gives everyone ways to build their own solutions. As Copilot takes on increasingly sophisticated work, access to trusted business context becomes essential.

Today, we are excited to share we are bringing business context from Fabric IQ into Microsoft Copilot, grounding your work in a shared understanding of the business. Microsoft Copilot customers can now tap into AI-powered insights from Fabric as part of their Copilot experience, without additional AI token costs. Fabric IQ in Copilot Chat and Cowork is generally available today, with integration into the new Code experience coming soon through the Frontier program.

For Power BI customers, this semantic foundation is already in place. Business definitions, key metrics, and organizational knowledge captured in trusted Power BI semantic models and reports can now directly inform decisions and actions in Microsoft Copilot. This allows Copilot users to ask business questions and receive AI-powered insights grounded in the semantic data layer their organization already trusts.

As Bogdan Crivat highlights in his blog, Bringing governed analytics into the flow of work, this is a key step toward conversational analytics that connects enterprise data, business context, and AI to help people make better decisions. Check out the following demo to see this in action:

The next evolution of Power BI: Agentic app creation

With more than 425,000 customers across every country and industry, Power BI has been the most widely used business intelligence platform in the market, helping users turn their data into insights. Today, we are excited to announce the next evolution of Power BI: bringing agentic app creation to Microsoft Power BI Desktop.

Business intelligence has traditionally followed a familiar pattern: analysts modeled data, built reports, and published dashboards for others to consume. Copilot in Power BI has made this process more conversational, helping users explore data and create and refine reports using natural language. Now, AI is enabling users to go beyond uncovering insights to build tools, workflows, and applications directly from their data.

The new agentic app creation experience in Power BI Desktop takes this a step further. Starting with a trusted semantic model, users can describe the application they need, generate it using natural language, preview and edit it in real time, and publish it to Microsoft Fabric without starting from a blank canvas.

While Copilot in Power BI helps you analyze data and build reports, this new experience enables you to create purpose-built data applications. These applications can accept inputs, write back data, preserve shared state, and support operational workflows.

This experience uses our open-source Rayfin technology to provide each application with a Fabric SQL database, authentication, and security. As an application grows, users can expand its functionality and hand it off to developers and IT teams without rebuilding it.

Watch the following demo to see the new experience in action:

Importantly, this experience isn’t limited to Microsoft Fabric capacity customers. Apps in Power BI will be available in preview in the coming weeks to Power BI Pro and Power BI Premium Per User customers as well as Microsoft Fabric capacity customers. This means Power BI Pro and Premium Per User customers, at no additional cost, will also have access to Fabric Apps and Fabric Database capabilities—up to 1 GB per app—along with enterprise-grade security and scale for hosting. Fabric customers can then extend these apps with other Fabric workloads, creating richer applications on their existing data and services.

To learn more about this feature and other innovations coming to Power BI, read Mohammad Ali’s blog, Power BI’s next chapter: The evolution of business intelligence.

Explore Microsoft Power BI features

Move from idea to production faster with Fabric Apps

AI can accelerate prototyping, but moving an application into production still requires teams to connect data, add business logic, manage infrastructure, and enforce governance. Fabric Apps closes this gap by giving developers a governed application layer on Microsoft Fabric.

Since the initial launch in June 2026, thousands of developers have used Fabric Apps to build AI-powered business applications, operational workflows, and custom experiences on governed data. Using the open-source Rayfin SDK and CLI, developers and coding agents can build application backends and deploy them to Fabric as Fabric Apps.

With the latest enhancements, developers can connect apps directly to Fabric warehouses, SQL databases, lakehouses, and Power BI semantic models without duplicating data, while preserving existing permissions and trusted business logic. New TypeScript backend functions, Secret Store, PostgreSQL support, private-by-default access, and built-in usage and performance metrics provide the services needed to take those apps into production.

Together, these capabilities give developers a faster path from idea to secure, governed, production-ready Fabric Apps while spending less time assembling infrastructure and more time building differentiated application experiences.

Check out what you can build with Rayfin:

Learn more about Rayfin by reading Sachin Patney’s blog, From prompt to production: What’s new in Fabric Apps.

Building an AI-ready data foundation with Microsoft Fabric

While Fabric IQ brings business context into Copilot, applications, and agents, that intelligence must first be created and maintained. Organizations need a foundation that can unify data across sources, transform and prepare it for analysis, and capture business meaning through semantic models and ontologies. Today’s Microsoft Fabric innovations make it easier to build this foundation from end to end.

Unify your data estate with Microsoft OneLake

As organizations scale AI, connecting data is no longer enough. Copilots and agents also need business context, including terminology, relationships, instructions, and domain knowledge, to deliver relevant answers and take informed action. Microsoft OneLake provides an open foundation for connecting data across clouds, applications, and platforms through mirroring and shortcuts.

Share governed data and context with IQ sharing

Today, we’re taking the next step with IQ sharing, now in preview. IQ sharing helps organizations securely share governed data and business context across teams, customers, partners, and ecosystems, making intelligence reusable beyond organizational boundaries. At launch, IQ sharing supports governed tables and files alongside Markdown agent instructions and RDF ontologies, with native support for Fabric IQ ontologies and Power BI semantic models on the roadmap.

EY, TomTom, Financial Fabric, and xMentium are already building integrations with IQ sharing. For example, TomTom is bringing its geospatial and transportation intelligence into Fabric, with available data products discoverable through the OneLake catalog.

Together, mirroring, shortcuts, and IQ sharing create an open data network that enables organizations to connect, access, and collaborate on governed data across teams, partners, and ecosystems. This extends OneLake beyond data integration to support reusable data products that power analytics and AI.

Expanding the OneLake ecosystem

We’re also expanding the reach of that open data network with the preview of bidirectional integration with Salesforce Data Cloud 360, the general availability of Google BigQuery mirroring, and deeper integration with Microsoft Dynamics 365 Business Central. Now, Salesforce data becomes part of the unified data estate without moving or duplicating it, making it available across Fabric for analytics and AI, including as business context for Fabric data agents. Together, these capabilities make it easier to work across platforms and clouds without duplicating data or building complex integrations.

Learn more about all the innovation coming to Microsoft OneLake by reading Dipti Borkar’s blog, What’s new in Microsoft OneLake and its rapidly growing ecosystem.

Get all your data in one place in Microsoft OneLake

Process and harmonize data more efficiently

Connecting data is only the first step. Organizations still need to prepare, transform, and operationalize data at scale. To help teams move faster from data to insight and action, we’re introducing data engineering agent in Microsoft Fabric, and new Copilot experiences in Fabric Real-Time Intelligence.

Delegate complex data engineering work to data engineering agents

As AI becomes part of the development process, data engineers are evolving from executing every task themselves to orchestrating intelligent systems. Fabric is taking the next step in that evolution with the data engineering agent, built on technology from Microsoft’s acquisition of Osmos earlier this year. Now in preview, the data engineering agent brings governed, autonomous execution to complex, long-running initiatives such as data platform migrations, lakehouse modernization, performance optimization, complex extracting, transforming, and loading (ETL), and data preparation.

Engineers define the desired outcome and establish guardrails. Within those boundaries, the agents then plan and execute the work autonomously, validate results and refine its approach, helping teams move complex data initiatives forward while keeping engineers in control.

Fabric data engineering agent is also designed for collaborative work that spans people and teams. Tasks inherit workspace permissions, enabling authorized team members to monitor progress, contribute context, respond to decisions, and work together on the same task.

And because data engineers work across multiple development environments, these capabilities extend across Fabric and developer tools, including GitHub Copilot, Microsoft Visual Studio Code, Codex, and Claude Code. Engineers can start, monitor, and steer the same work from the tools they already use without losing context or progress.

Learn more about the Fabric data engineering agent in Bogdan Crivat’s blog, Bringing governed analytics into the flow of work.

Simplify working with real-time data with Copilot

Organizations increasingly need to act on live operational signals, not just historical reports. New Copilot capabilities in Real-Time Intelligence help teams understand, monitor, and manage real-time data using natural language. Users can now create Real-Time Dashboards by describing what they want to understand, while Copilot assists users with eventhouse management and administrative tasks such as creating tables, configuring policies, managing schema, and inspecting cluster state.

New schema recommendations and optimization capabilities further help organizations improve performance and reduce costs, while the operations agent accelerates troubleshooting with AI-powered root cause analysis and actionable recommendations. Learn more about Real-Time Intelligence innovations in Yitzhak Kesselman’s blog, Microsoft Fabric: The foundation for the enterprise that thinks and acts as one.

Curate context with Fabric IQ

With data unified and prepared, organizations need a way to capture the business meaning, relationships, rules, and operational context that AI depends on. Fabric IQ provides this shared intelligence layer, extending governed business context across Microsoft Copilot, Microsoft Foundry, GitHub Copilot, and custom applications to help agents reason over a common understanding of the business.

Accelerate ontology creation and governance

Today, we are making it easier to define and govern this context layer. We are introducing a new agentic experience to create ontologies from semantic models, OneLake data, and other context documents, reducing the effort required to capture business concepts and relationships.

You can define rules in natural language, connect them to ontology entities, properties, and relationships, and make them part of the shared context people and agents use to navigate business operations consistently. You can also carry Power BI measures into your ontology, allowing you to reuse these established metrics.

We’re also affirming our commitment to Apache Ossie (incubating), a community-led effort to establish a vendor-neutral standard for exchanging semantic metadata across analytics, AI, and BI platforms. Working with Snowflake and the broader industry, we’re helping make semantic context open and reusable across platforms.

Together, these capabilities make it easier to maintain shared business meaning and help agents reason over governed data with greater accuracy and consistency. Learn more about Fabric IQ in Yitzhak Kesselman’s blog, Microsoft Fabric: The foundation for the enterprise that thinks and acts as one.

Create and manage agents in Fabric

The value of a shared intelligence foundation comes when agents can use that context to deliver real outcomes. New enhancements across Fabric agents make it easier to build, govern, and operationalize AI experiences across Microsoft Fabric and other AI platforms.

We are deepening the integration between Fabric data agents and ontologies in Fabric IQ, enabling more accurate and explainable answers grounded in business concepts and relationships. The build agent with AI mode can now use semantic models, documentation, glossaries, and data dictionaries to generate richer data agent experiences with less manual configuration. Operations agents are adding pre-approved actions in preview and bringing root-cause analysis to general availability, helping teams investigate issues, identify likely causes, and automate repeatable responses while maintaining human oversight and control. Learn more about these updates by visiting Bogdan Crivat’s blog, Bringing governed analytics into the flow of work, and Yitzhak Kesselman’s blog, Microsoft Fabric: The foundation for the enterprise that thinks and acts as one.

Operate Fabric with greater visibility and control

As organizations place more workloads on a unified data platform, operational maturity becomes as important as analytical capability. Teams need to understand what is happening across jobs, capacities, workspaces, and services—and resolve issues before they affect the business.

Introducing new observability capabilities in Microsoft Fabric

Observability in Fabric, now in preview, is a new set of platform capabilities designed to help organizations move from reactive troubleshooting to proactive operations. Spanning workspace monitoring, the monitor hub, and operations agents, these new observability capabilities provide a unified view of the Fabric estate, making it easier to detect issues early, investigate root causes with AI assistance, and manage operations from a single experience.

The new workspace monitoring experience allows you to consolidate telemetry in a single eventhouse for multiple workspaces, simplifying cross-workspace monitoring. You can even make the data available in other destinations with custom endpoints and control the exact retention rate and caching policy you need.

We’ve also enhanced the monitor hub in Fabric with deeper visibility into jobs, capacities, and workloads through built-in views, alerts, and AI-powered insights. New Activator-powered job alerts notify teams of job failures and successes, while a new capacity view helps monitor consumption and headroom. In addition, we’ve added new investigation capabilities to operations agents, helping data professionals and administrators diagnose issues faster by autonomously identifying root causes and recommended actions.

Together, these capabilities reduce the effort required to identify problems, improve reliability, and keep data and AI workloads running smoothly.

Check out the demo below to see observability in action:

Pay only for what you consume with on-demand billing

Visibility is only part of the equation. Organizations also need flexible, predictable ways to align infrastructure costs with usage as data and AI workloads scale.

Building on Autoscale Billing for Spark, on-demand billing expands consumption-based billing across Fabric workloads, allowing you to pay only for the compute you use, automatically scaling resources up and down based on your demand. Fabric zero-provisioned adds to on-demand billing by allowing you to get started with Fabric and OneLake without an upfront capacity commitment.

To learn more about observability in Fabric, on-demand billing, and other innovation coming to the Fabric platform, read Kim Manis’s blog, Build, deploy, and govern Microsoft Fabric at scale.

Manage, optimize, and scale your database estate

Building intelligent applications requires more than powerful AI models. Organizations also need databases that can scale with demand, tools to manage growing data estates, and intelligent operations that keep systems running reliably.

Today, we’re introducing new capabilities across Database Hub, Database Agents, and Microsoft Azure SQL Database that help organizations build, manage, and optimize the data foundation behind the next generation of intelligent applications.

Centrally manage your database estate with the Database Hub in Fabric and database agents

As developers build more applications and operational workloads move into Fabric, managing a growing database estate becomes just as important as building applications. Organizations need a unified way to monitor, govern, and optimize these databases.

Building on its introduction at FabCon & SQLCon Atlanta, Database Hub in Fabric is now in preview. It provides a centralized control plane for managing SQL Server, Microsoft Azure SQL, PostgreSQL, Azure Cosmos DB, and SQL database in Fabric. From a single experience, administrators can monitor health, assess risk, enforce governance, and gain visibility across their entire database estate.

Additionally, we are introducing database agents for SQL and PostgreSQL on Azure, which will soon be available in preview. These AI-powered specialist agents, accessible in the Database Hub in Fabric and VS Code, continuously observe and analyze database signals, helping administrators investigate issues, understand performance bottlenecks, identify optimization opportunities, and accelerate troubleshooting. By bringing AI-assisted operations directly into a unified management experience, teams can move from insights to action faster while improving reliability, performance, and security.

Together, these innovations provide the operational foundation for intelligent applications across Microsoft, helping organizations manage their data estate with the same simplicity, scale, and intelligence that powers analytics and AI in Microsoft Fabric.

Learn more about the Database Hub and database agents in Shireesh Thota’s blog, FabCononnecting apps, databases, and AI on one foundation & SQLCon.

Bringing greater scale, efficiency, and AI innovation to Azure SQL Database Hyperscale

Intelligent applications place new demands on databases, requiring greater scale, efficiency, and built-in support for AI-powered scenarios. We’re introducing new innovations in Azure SQL Database Hyperscale designed to help developers reduce costs, scale demanding applications, and build AI-powered experiences using familiar SQL tools.

Serverless auto-pause for Azure SQL Database Hyperscale, now in preview, automatically pauses compute during periods of inactivity and resumes when workloads return, helping reduce costs for development, test, and intermittent workloads. We’re also increasing elastic pool density to support up to 50 databases per pool and making 192 vCore compute for Azure SQL Database Hyperscale generally available, enabling greater scale and concurrency for mission-critical applications.

In addition, we’re announcing the general availability of DiskANN vector indexes for Azure SQL Database Hyperscale, Azure SQL Managed Instance, and SQL database in Fabric, bringing high-performance vector search directly into the database engine. Developers can build recommendation engines, semantic search, and retrieval-augmented generation (RAG) applications without moving data to a separate vector store.

Enable sovereign data across customer-controlled environments

Organizations need the flexibility to run data platforms where performance, regulatory, and operational requirements demand. Microsoft is expanding where customers can run Azure and SQL Server capabilities, enabling modern workloads across sovereign, customer-controlled data estates—whether on the cloud, edge, or in disconnected environments.

SQL Server on Azure Local is now generally available, bringing SQL Server and Azure capabilities to local environments. Organizations can run mission-critical workloads closer to their applications and operations for low-latency, high-performance access to data while maintaining control over where data resides. In addition, SQL Server on Azure Local Disconnected Operations (ALDO) is also now generally available, enabling the same platform and experience in environments where cloud connectivity is unavailable, restricted, or intentionally disconnected.

Whether supporting regulated industries, operating at the edge, or running business-critical systems in disconnected environments, customers can now bring modern Azure and database capabilities closer to their data while maintaining the performance, control, and flexibility their workloads require.

Finally, Microsoft Fabric is expanding to Microsoft 365 Government Community Cloud High (GCC High) customers, supporting organizations that require United States sovereign cloud environments and compliance.

Learn more about all the innovation we are bringing to our database offerings by reading Shireesh Thota’s blog, Connecting apps, databases, and AI on one foundation.

See more Fabric and Azure Database innovation

AI transformation will not be defined by how many agents organizations create, but by how effectively those agents understand the business and work together to deliver outcomes. The organizations that build a trusted, connected data foundation now will be best positioned to lead.

For a deeper look at the updates above and to see what else is new this month, visit the Fabric September 2026 Feature summary blog, the Power BI September 2026 feature summary blog, and the latest posts on the Fabric Updates channel and the Azure Data Tech Community blog channel.

Explore additional resources for Microsoft Fabric

Sign up for the Fabric free trial.View the updated Fabric Roadmap.Try the Microsoft Fabric SKU Estimator.Visit the Fabric website.Join the Fabric community.Read other in-depth, technical blogs on the Microsoft Fabric Updates Blog.

Read additional blogs by industry-leading partners

Emergent Software: Microsoft IQ Explained: How Microsoft Is Building Context for AI Agents

Acuvate: Microsoft Fabric IQ Ontology for Enterprise AI Agents

Acuvate: Scaling Enterprise AI: Data, Governance, Real-Time Intelligence & More

Bismart: Fabric IQ in Microsoft Fabric: Semantic Layer for Artificial Intelligence

Element61: Fabric IQ: When your Data needs to speak Business

Get started with Microsoft Fabric

The post FabCon and SQLCon 2026 in Barcelona: Building the data foundation for Microsoft Copilot and agents appeared first on Microsoft Fabric Blog.

Today, we are excited to announce the availability of Microsoft Fabric in Microsoft 365 Government Community Cloud High (GCC High). Beginning September 2, 2026, Microsoft Fabric will be available in public preview for GCC High customers, with general availability starting October 1, 2026. Feature availability at public preview and general availability will vary by workload and expand over time. Visit the Microsoft Fabric for US Government GCC High customers Learn page for current details.

To realize the full potential of AI, agencies need a modern data foundation that brings together analytical, operational, transactional, structured, and unstructured data while meeting the security, compliance, and governance requirements of regulated environments.

That is the challenge Microsoft Fabric is designed to address. As Microsoft’s unified data and AI platform, Fabric helps organizations unify their data, establish shared business context, and move from isolated AI experiments to production-ready agent systems grounded in trusted organizational knowledge.

Learn more about Microsoft Fabric for US Government GCC High
Experience a unified data and AI platform designed for the next frontier of AI
Microsoft Fabric brings together data integration, analytics, databases, real-time intelligence, and business intelligence into a single open SaaS platform. By unifying data in OneLake and connecting people, data, and workloads on a common foundation, Fabric helps organizations achieve faster insights, more productive teams, and optimize costs on an enterprise-grade platform.

For government organizations, this provides a modern data foundation for analytics, AI, and intelligent agents on a single, integrated platform. Instead of managing separate tools for data movement, storage, analytics, and reporting, agencies can bring these capabilities together in a single environment that helps teams collaborate, simplify governance, and prepare data for analytics, AI, and intelligent agents.

Building this kind of AI-ready foundation typically involves four key steps:

Unify your data estate: Eliminate silos and reduce architectural complexity by bringing data together.
Process and harmonize data: Stream, integrate, and transform historical and real-time data to make it AI-ready.
Create semantic meaning: Add business context to data so agents understand data the same way your teams do.
Empower AI agents to act: Use unified, context-rich data to automate workflows, accelerate decisions, and drive action.
Microsoft Fabric unifies data integration, databases, analytics, business intelligence, and AI on a single platform while delivering the capabilities organizations expect from category leaders. Microsoft is recognized as a Leader in the 2026 Gartner® Magic Quadrant™ for Analytics and Business Intelligence Platforms and in the 2025 Gartner® Magic Quadrant™ for Data Integration Tools, Cloud Database Management Systems, and Cloud AI Developer Services.

Unify your data estate with Microsoft OneLake
Preparing data for AI often starts with a simple challenge: finding and connecting all the data an organization already has.

Most government data estates span multiple systems, clouds, departments, and applications. Data teams spend significant time moving, copying, synchronizing, and managing data before they can use it for analytics or AI. This complexity creates additional cost, operational overhead, and governance challenges.

At the center of Microsoft Fabric is Microsoft OneLake, a single, unified data lake that helps organizations bring together their entire data estate. With zero-copy, zero-ETL tools in OneLake, agencies can connect data across clouds, on-premises systems, and third-party platforms without creating unnecessary copies or duplicating data across multiple environments. For example, Lumen, a leader in enterprise connectivity, cut 10,000 hours of manual effort.

We used to spend up to six hours a day copying data into SQL servers. Now it’s all streamlined…OneLake allowed us to ingest once and use anywhere.

Chad Hollingsworth, Cloud Architect at Lumen
This approach reduces data silos, simplifies architecture, and creates a common foundation that analytics, reporting, AI applications, and agents can all leverage. By bringing data together in one place, organizations can spend less time managing infrastructure and more time extracting value from their information.

Process and harmonize data
Unifying data is only the beginning. To support AI and advanced analytics, organizations also need to prepare, transform, and continuously refine their data.

Microsoft Fabric provides a complete suite of analytics capabilities that help organizations ingest, process, analyze, and visualize data across the entire lifecycle. Data engineers can build pipelines, data scientists can develop models, analysts can create reports and dashboards, and operational teams can monitor live streams of information, all on a shared platform operating over a common data foundation.

Because these capabilities are integrated within Fabric, organizations can move seamlessly from raw data to analytics, business intelligence, and AI applications without stitching together multiple disconnected services.

Instead of managing fragmentation, my team now focuses on building reliable patterns that scale with closely integrated capabilities like Fabric Data Warehouse and Fabric’s native executive engine for Spark. The shift reduced costs and operational friction and restored confidence.

Nagaraju Gutlapalli, Head of Data Engineering, Bajaj Finserv
For government organizations, this creates a more efficient path from data collection to actionable insight, helping teams respond more quickly to changing operational needs while maintaining trust in the underlying data.

Create semantic meaning
One of the biggest challenges with AI is that data alone is not enough. To generate meaningful insights and take useful actions, AI systems need to understand how an organization operates, including its business processes, policies, operational state, and institutional knowledge.

Fabric helps address this challenge through Fabric IQ, the intelligence layer for enterprise knowledge and operations. Fabric IQ brings together unified data in OneLake, business intelligence through semantic models and metrics, and operational intelligence. Together, these capabilities create a shared knowledge foundation that gives data consistent business meaning across the organization.

For government organizations, this is particularly important because useful AI outcomes often depend on understanding complex relationships between people, programs, assets, operations, and policies. By combining data with institutional and operational knowledge, Fabric helps ensure AI systems are grounded in trusted organizational context rather than isolated datasets or technical schemas.

The result is a shared intelligence foundation that people and AI can understand, reason over, and act upon. This foundation enables trusted AI experiences, intelligent applications, and specialized agents that can analyze information, recommend actions, automate workflows, and support mission-critical decisions.

Empower AI agents to act
As organizations move beyond AI assistants and toward intelligent agents that can reason, automate work, and take action, the quality of the underlying data foundation becomes increasingly important.

Microsoft Fabric provides the foundation for these next-generation AI experiences by bringing together unified data in OneLake, analytics across the Fabric platform, and enterprise knowledge through Fabric IQ. Together, these capabilities enable agents to access trusted data, understand business context, reason over current conditions, and take informed action.

Organizations can connect data and knowledge from Fabric to AI experiences built with Microsoft Copilot Studio, Microsoft Foundry, Microsoft 365 Copilot, and custom applications, helping ensure agents operate with a consistent understanding of enterprise data and operations.

Using Fabric and Foundry Agent Service, we’ve built agents that allow us to talk to our data, ask personalized questions, and uncover insights based on role or function.

Maureen Tan, Head of AI Center of Excellence, NTT DATA
For government agencies, this creates new opportunities to accelerate analysis, improve operational efficiency, automate mission-critical processes, and empower employees with AI experiences grounded in trusted organizational knowledge.

Getting started with Microsoft Fabric in GCC High
The availability of Microsoft Fabric in GCC High represents an important milestone in bringing Microsoft’s data and AI platform to government customers operating in regulated environments.

Organizations can begin exploring and adopting Fabric capabilities using their existing Power BI Premium capacities. Both Power BI and Fabric workloads will consume from the same capacity, enabling you to start using Fabric workloads immediately while continuing to run existing Power BI reports, dashboards, and semantic models without interruption.

For organizations already using Power BI Premium, Microsoft Fabric is available as part of their existing capacity. To learn more about the changes coming to your Power BI Premium environment, visit the Microsoft Fabric for US Government GCC High customers Learn page.

For GCC High organizations that do not currently have Power BI Premium, Microsoft Fabric capacity is available for purchase starting today.

Not all Microsoft Fabric capabilities will be available at launch. To view the complete list of supported features and the latest availability information, visit the same Fabric in GCC High Learn page. Please continue checking back as many more features will continue to be released over the following months.

Building the data foundation
As agencies continue their AI transformation journeys, success will increasingly depend on the strength of their data foundation. By helping organizations unify their data estate, prepare data for analytics and AI, add business context, and create trusted AI experiences, Microsoft Fabric provides a platform designed for the next generation of government innovation.

The future of AI starts with data. With Microsoft Fabric in GCC High, government organizations can begin building that foundation today.

The post Microsoft Fabric in GCC High: Building the data foundation for AI appeared first on Microsoft Fabric Blog.

Even how I start my day has changed. I built what I think of as a “chief of staff” agent that brings together my calendar, key metrics, customer context, and recent communications into a single briefing—turning what used to take close to an hour into just a few minutes with a clear view of what matters most.

I am seeing the same shift across my teams. They are not just using AI to assist with tasks—they are redesigning how work gets done, with greater focus on higher-value work that requires judgment and creativity.

This is why AI agents are quickly becoming a core building block for how organizations operate. The question is no longer whether they can help, but where they can be trusted to act today—and how we unlock more complex scenarios.

We partnered with MIT Technology Review Insights on new research, the Agent Confidence Index, which explores exactly that. Based on a survey of 300 global technology experts, the report ranks 101 tasks across data, AI, and cloud workflows based on respondents’ confidence in agents acting on their behalf. It provides a clear view of how the agentic frontier is unfolding across organizations around the world.

Data workflows are a breakthrough domain for agent adoption

The results point to a clear pattern. Confidence is highest when tasks are well-defined, measurable, and grounded in structured data. It is one of the reasons data workflows have emerged as the leading domain for agent adoption, including areas such as data quality monitoring, visualization anomaly detection, real-time data stream monitoring, and data profiling.

Teams are actively delegating these tasks to agents, observing the outcomes, and refining how those agents operate over time. Confidence in these tasks has now moved beyond potential alone. It is built through experience, iteration, and measurable results.

These workflows share a set of characteristics that make them well-suited for agent execution. They are well-scoped, high-volume, and operate on structured data. They also produce outputs that are observable and, in many cases, reversible. This makes it easier for teams to validate results, iterate quickly, and build trust in how agents perform.

For data teams, this is the ideal starting point. Agents reduce the manual effort that has traditionally been required to maintain data pipelines, monitor systems, and generate insights. There has always been a significant amount of toil in data analysis, and agents are helping remove much of that friction. Teams can move faster, respond earlier, and focus on higher-value work.

We are seeing this play out in practical ways. Even simple workflows like preparing for the day, reviewing metrics, or getting ready for customer engagements can now be reimagined with agents that bring together calendar, communications, customer context, and business performance. What used to take meaningful time and effort can now be consolidated into a few minutes with a more complete and consistent view.

These early wins do more than drive efficiency. They create a feedback loop. When teams can see how agents perform, measure outputs, and refine prompts, inputs, and context, confidence grows quickly. That is what enables organizations to expand from well-understood data scenarios into broader, more complex use cases.

As complexity increases, confidence shifts

As organizations push beyond these initial scenarios into more complex asks, the picture changes. Confidence drops as tasks become more complex, more interconnected, and more dependent on business judgment. That gap tells us something important.

The next phase of agentic AI is not just about improving models. It is about building the foundation around the models—the right context to train the agents, along with sophisticated observability to monitor their actions—enabling organizations to increasingly trust agents to handle new areas of the business.

Lower-confidence tasks in the survey include areas like cross-cloud data synchronization, database migration planning, feature engineering automation, and legacy system modernization. These are not just technical problems. They are coordination problems that span systems, teams, and business priorities.

What makes these tasks harder is not just their complexity. These often require coordinating long, multi-step workflows, such as database migration and planning. Many of these scenarios do not have a single correct answer, even for a human expert. They require understanding business priorities, interpreting incomplete information, and making decisions based on nuance.

Even a seemingly simple request can depend on assumptions that are obvious to a human but invisible to an agent. If you ask for the top customers by revenue, you still need to know which definition of customer to use, how revenue is calculated, and which time frame applies. Without that shared understanding, the result can vary significantly.

This is why the same pattern shows up repeatedly in practice. When an agent produces an incomplete or incorrect answer, it is often not because the model lacks capability. Instead, it is because the agent does not yet have the business context required to answer the question correctly.

At scale, this creates a real challenge. If each agent has to relearn how the business operates, where data resides, and what rules apply, organizations cannot effectively scale their use of AI. The bottleneck is no longer model capability. It is the lack of shared, consistent data context.

Building trusted agents on shared data context

To move beyond isolated use cases, agents need a common understanding of the business: the definitions of customers, orders, products, revenue, and the relationships between them. Historically, people have filled in this context through experience and interpretation. But as agents take on more responsibility, this gap becomes more pronounced. Without a consistent, shared view of how the business operates, agents struggle to reason accurately, coordinate across workflows, or take reliable action.

That’s the challenge we are solving with Microsoft IQ, which brings together different layers of enterprise context. Web IQ adds real-time global context from the web. Work IQ provides context around people, meetings, documents, and collaboration. Foundry IQ connects enterprise knowledge and processes. Fabric IQ brings together business and operational data into a unified semantic foundation.

This approach mirrors how organizations onboard people. When you bring in a new team member, you provide context about how the organization works, what metrics matter, how decisions are made, and what processes to follow. Agents require that same grounding through Microsoft IQ. Without it, they operate in isolation.

For data teams, Fabric IQ plays a critical role in delivering that shared understanding. It provides a consistent semantic layer across data, allowing agents to work with business entities, relationships, rules, and metrics rather than disconnected tables and schemas.

This shift is foundational. Instead of trying to infer meaning from raw data, agents can operate on a shared model that reflects how the business actually runs. That enables more accurate insights and more reliable decision support.

Just as importantly, it enables coordination. When agents operate on the same context, they can work across workflows, share understanding, and contribute to larger processes. Confidence grows when data, tools, and agents all operate on that same foundation, rather than being stitched together across disconnected systems.

Real-time data brings agents closer to action

Context also needs to be current.

Many of the highest-value data scenarios involve responding to live signals. Monitoring pipelines, detecting anomalies, supporting operations, and enabling timely decisions all depend on having up-to-date information. As organizations invest in real-time data platforms, they enable agents to operate with real-time context. Instead of analyzing what happened in the past, agents can surface insights and support decisions as events unfold.

While Fabric IQ provides the shared definitions, relationships, and context that ground reasoning, Real-Time Intelligence (RTI) is Microsoft’s answer to operational intelligence, bringing in live signals, events, and real-time state across the business. Together, these layers form a closed loop—where agents not only understand what is happening, but act on it as it unfolds, with decisions grounded in consistent context and executed against current conditions.

Data agents and operations agents in Fabric then reason over shared live context, make decisions based on policy, and take action in the moment.

These capabilities enable agents to begin shifting from analysis to action. They are not just helping teams understand what happened but helping them respond to what is happening now.

Trust is built through visibility and control

As agents take on more responsibility, trust becomes critical.

Most organizations are taking a pragmatic approach to building this trust. A majority, 59%, plan to keep humans actively involved in decision-making, particularly for scenarios with higher stakes.

At the same time, 53% are increasing observability by closely monitoring agent activity and tracing how decisions are made. In practice, this means agents are used to analyze data, surface insights, and recommend next steps, while humans remain responsible for final decisions when outcomes carry meaningful impact or are difficult to reverse.

At the same time, governance and observability need to be built in from the start. This includes clear policies, defined guardrails, and the ability to monitor how agents behave in practice. Observability is not just about tracking activity. It is about understanding how outputs align with intent and continuously evaluating and improving how agents perform.

This is where capabilities like Microsoft Agent 365 become increasingly important. As organizations scale their use of agents, they need a centralized way to monitor agent activity, trace decisions back to their inputs, and understand how agents are operating across workflows. These tools provide the visibility needed to safely expand agent autonomy, while ensuring that governance and accountability remain intact.

These capabilities are quickly becoming a discipline in their own right. As organizations build and operate agent systems, they are developing new practices around evaluation, validation, and control to ensure consistent and reliable outcomes at scale.

The path forward

The path to agentic AI is becoming clearer. Organizations should start where confidence is already high, focusing on structured data workflows where value is immediate and outcomes are measurable.

From there, the focus shifts to building the foundation that enables more complex scenarios. This means investing in unified data platforms, defining shared business context, and implementing governance and observability as first-class capabilities.

As agents take on more of the repetitive and high-volume work, the role of humans shifts. More of the remaining work becomes centered on judgment, strategy, and decision-making. That makes having the right data context even more critical.

The long-term opportunity extends far beyond individual automations. It is about creating systems where agents can work together, grounded in a shared understanding of the business, to support decisions and execute across workflows.

I touched on the implications for data professionals, but for those interested in what this research means for builders and traditional developers, my colleague Amanda Silver has written a companion perspective—check her blog for a deeper dive.

Next steps

• Download the full Agent Confidence Index from our partners at MIT Technology Review Insights. It’s a free, ungated deep dive into all 101 tasks, broken out by role and workflow, with the full patterns and reasoning behind where confidence is strongest and where the frontier is expanding fastest.
• Learn more about how Microsoft IQ, Fabric IQ, and Microsoft Agent 365 can help you build a unified, trusted foundation for your agents. Catch up on everything we announced at Microsoft Build for the latest on agentic capabilities across the stack.
• If you’re at the AI Engineer World’s Fair this week, stop by the Microsoft booth. We’re having open, direct conversations with technical leaders about where agents are proving real value today—focused on what’s working and what teams are still learning.

See the Agent Confidence Index

View the report

The post Why data teams are emerging as leaders in AI agent adoption appeared first on Microsoft Fabric Blog.

Following our record-breaking gathering of more than 4,000 data professionals in Vienna last year, FabCon Europe is back and bigger—with 130+ expert-led sessions, 100+ speakers, and 10+ hands-on tutorials spanning the entire Fabric and SQL ecosystem. And once again, FabCon and SQLCon are co-located, so a single registration gives you access to the best of Fabric and SQL training, all under one roof.

From hands-on technical sessions to customer-led stories, there’s something for every data professional, presented by our Microsoft team and partners alike. 

To help you plan your week, I’m sharing a few of my top picks across the tracks I’m most excited about this year.

AI, data agents, and Fabric IQ

AI is at the heart of everything we’re building, and these sessions show what it looks like to put intelligent agents to work on your own enterprise data. At Microsoft Build 2026, we announced the general availability of Fabric IQ—these sessions are a great opportunity to see it in action.

• Build the next generation of intelligent data agents in Microsoft Fabric—Misha Desai, Avrilia Floratou. Join this deep dive into next-generation agent capabilities, including support for unstructured data, graph reasoning, and the latest NL2SQL innovations. If you want to understand where intelligent data agents are headed, start here.
• Fabric IQ End-to-End: The Complete Enterprise AI Platform—Chafia Aouissi, Yael Schuster-Davidi. Fabric IQ creates a unified, governed foundation for enterprise AI agents. This end-to-end walkthrough shows how the pieces fit together so agents can answer more complex questions with confidence.
• From Insight to Action – Translytical Taskflows and AI in Microsoft Fabric—Nadim Abou-Khalil. See how to close the loop between analytics and action, combining real-time workflows and AI-powered automation, so insights don’t just inform decisions—they help trigger them.
• Fabric IQ + Foundry: The Semantic Backbone of Enterprise AI Agents—Hugo Barona. Learn how semantic grounding improves agent reasoning and reduces hallucinations, and why a strong semantic layer is the backbone of trusted enterprise AI.
• Building Enterprise AI Agents on Microsoft Fabric: Architecture, Security and Production Lessons—Leon Gordon. A real-world blueprint for deploying enterprise-grade AI agents in regulated environments—covering the architecture, security, and hard-won production lessons you’ll want before you ship.

Real-time intelligence

When your data is moving, your insights should be too. These sessions bring Fabric Real-Time Intelligence to life with live telemetry, streaming pipelines, and operational use cases.

• From Real-time Data to Custom machine learning-driven Insights—Sónia Cruz, Rita Sousa. Turn streaming data into intelligent decision-making with custom machine learning models and see how Fabric helps you move from raw events to predictions in real time.
• Every turn you take, every move you make – Agents operating on real-time ship movements—Frank Geisler, Sander van de Velde. One of the most engaging real-world sessions on the agenda: see operational intelligence in action as agents reason over live ship-movement telemetry and automate decisions in real time.
• Turning Database Changes into Real-Time Intelligence with Fabric Eventstreams—Arindam Chatterjee, Xu Jiang. Learn how to convert OLTP changes into real-time, AI-ready workloads using Eventstreams—without requiring complex pipelines.

Data engineering, lakehouse, and integration

The foundation matters. These sessions are full of practical, production-tested patterns for modernizing your estate and orchestrating workloads at scale.

• From Legacy to Fabric: Migrating a 10-Year Data Warehouse Without Lift-and-Shift—Florian Pujol, Lydia Helle. A practical playbook for modernizing a legacy data platform thoughtfully—without simply lifting and shifting legacy challenges into a new environment.
• Choosing the Right Data Integration Approach in Microsoft Fabric—Gaston Cruz, Javier Villegas. Pipelines, shortcuts, Spark, or warehouses? Walk away with a clear decision framework for choosing the right integration approach for each scenario.
• From Chaos to Control: Orchestrating Lakehouse Workloads in Microsoft Fabric—Ásgeir Gunnarsson. Real-world orchestration patterns to bring order to production lakehouse environments and keep your workloads running predictably.
• Zero-Copy, Multi-Cloud Fabric: OneLake Shortcuts + Mirroring as the Fast Track to AI and Real-Time—Terry Russell. Discover modern architecture patterns that unify multi-cloud data with OneLake shortcuts and mirroring—your fast track to AI and real-time scenarios without duplicating data across systems.

Data warehousing and Fabric SQL

For the T-SQL developers and data warehouse professionals, these sessions cover what’s new, how to unify your estate, and how to keep everything running smoothly at scale.

• What’s New in Fabric Data Warehouse for T-SQL Developers—Jovan Popovic, Salil Kanade. Get the latest developer capabilities for building modern analytics with the SQL skills you already have.
• It’s Not Either–Or: Building an Intelligent Data Estate with Fabric Data Warehouse and Fabric SQL—Matthias Nohl. Learn how to unify transactional and analytical workloads into a single, AI-ready architecture—without trade-offs.
• Monitoring Fabric Data Warehouse at Scale—Sam Debruyn. Practical tools and techniques for optimizing warehouse performance and reliability when operating at scale.

SQL databases

SQL continues to evolve for the era of AI, and these sessions show how it’s becoming more intelligent, faster, and more capable than ever.

• Azure SQL Hyperscale: The Cloud Database for the era of AI—Bob Ward, Borko Novakovic. Hear why Hyperscale is becoming the default choice for modern cloud databases, and what that means for your AI-ready applications.
• Vector Search in SQL Server 2025 – Basics and Beyond—Ben Weissman. Bring AI-powered semantic search directly into SQL, from foundational concepts to advanced techniques.
• Mastering Performance for Microsoft SQL with AI—Erin Stellato, Anna Hoffman. See how AI is accelerating troubleshooting and performance tuning, helping you identify and resolve issues faster than ever.
• Azure SQL or Fabric SQL: Deploying Infrastructure and Databases as Code—Rob Sewell, Jess Pomfret. Learn how to automate database and infrastructure deployment using CI/CD pipelines, enabling version‑controlled, repeatable, production-ready workflows without manual configuration.

Governance and security

Trusted data is the foundation for trusted AI. These sessions cover how to govern, protect, and secure your estate end-to-end.

• OneLake security: deep dive and what’s new—Aaron Merrill, Cristian Petculescu. Go inside how unified security works across every Fabric workload, and get the latest on what’s new.
• Securing Your Data Estate with Purview—Marthe Moengen. An end-to-end approach to governance, compliance, and data protection across your Fabric estate.

Don’t miss FabCon TV

Can’t get enough behind-the-scenes energy? FabCon TV continues on YouTube, with new episodes filmed in Atlanta rolling out each week—featuring insights, previews, and voices from across the community. It’s a great way to get into the FabCon spirit before you arrive in Barcelona. 

Connect with the community that’s building the future

One of my favorite parts of every FabCon is watching this community come together—Microsoft product teams, MVPs, partners, practitioners, and first-time attendees, all working towards a shared goal: solving real-world challenges and helping each other learn and grow. Whether you’re deep in a hands-on session, swapping ideas in a hallway conversation, or connecting at a networking event, FabCon is where your ideas turn into reality.

With so much new innovation across Fabric and SQL to share—and so much to learn from each other—this year’s event is one you won’t want to miss.

Explore the FabCon Europe 2026 programme and start building your agenda. We can’t wait to see you in Barcelona!

The post FabCon Europe 2026: The sessions we’re most excited to bring to Barcelona appeared first on Microsoft Fabric Blog.

Data professionals have always worked in a fast-moving field, but the pace today is fundamentally different. Every day, the world generates roughly 400 million terabytes of data, and nearly 90% of the world’s data has been created in just the last two years.

This shift is also changing how data professionals work across platforms like Microsoft Fabric, Azure Databases, and SQL-based applications, where analytics, operational data, and AI development are increasingly connected.

For data engineers, analysts, and developers working across these environments, AI is rapidly reshaping how work gets done. Microsoft’s Work Trend Index finds that 75% of knowledge workers are already using AI at work, with many adopting it in just the last six months. This shift is not incremental; it is redefining how people build, analyze, and make decisions with data.

The opportunity is clear. Organizations that combine AI adoption with workforce readiness are already seeing measurable returns. Recent research shows businesses reporting multiple-fold returns on AI investments, reinforcing that value comes not just from deploying technology, but from enabling people to use it effectively.

Why skilling matters more than ever

Across industries, leaders are investing heavily in data platforms and AI capabilities. But technology alone isn’t enough. Research consistently shows that organizations that pair AI investments with structured workforce skilling are far more likely to see real returns on those investments.

We see this firsthand at Microsoft. Demand for data and AI learning continues to grow across engineers, analysts, developers, and AI practitioners. When people are given the time, tools, and community to build new skills, adoption accelerates and innovation follows.

That’s why Microsoft continues investing in accessible, community-driven skilling opportunities designed to help professionals build practical data and AI skills faster.

In practice, that means building skills that go beyond a single tool; learning how to unify data in Fabric, work with operational data in Azure Databases, and developing AI-powered applications using SQL. These are the capabilities that enable teams to move from experimentation to real business impact.

Data Days is back and bigger than ever

Back for its second year, Data Days is a global, community-driven virtual skilling event designed to help you build practical skills across the Microsoft data and AI platform—bringing together learning paths that span Fabric, Azure Databases, and SQL-based AI development. It brings together training, certification prep, contests, and self-paced learning across data engineering, analytics, and AI, making it relevant whether you work in Fabric, build on Azure, or develop AI apps.

Running June 15 through August 7, 2026, Data Days is designed specifically for those who want to grow their skills and advance their careers in data and AI.

Data Days is not limited to Microsoft Fabric alone. It brings together learning across data engineering, analytics, and AI, making it relevant whether you work primarily in Fabric, Power BI, Azure SQL, or modern AI-enabled data workloads. You can participate live, learn on demand, or focus on specific certifications or topics that matter most to you.

Together, these learning paths reflect how modern teams build a unified, governed data and AI estate across data, analytics, operational data, and AI development.

What to expect

Whether you’re building expertise in a specific area, or exploring new roles and technologies, this year’s Data Days offers a flexible mix of learning, certification support, and community-led experiences designed to help you grow.

• Certification skilling and exam prep
  • Get guidance to help you decide which certification aligns best with your role and goals. Live and on-demand sessions will help you prepare for key Microsoft data certifications, including:
    • Microsoft Certified: Power BI Data Analyst Associate (PL-300)
    • Microsoft Certified: Microsoft Fabric Analytics Engineer Associate (DP-600)
    • Microsoft Certified: Microsoft Fabric Data Engineer Associate (DP-700)
    • Microsoft Certified: SQL AI Developer Associate (DP-800)
• Certification exam vouchers
  • A limited number of 100%-off exam vouchers will be available for DP-600, DP-700, and DP-800, while supplies last.
• Study groups led by the community
  • Local and virtual study groups, hosted by user groups around the world, will provide structure, accountability, and peer support as you prepare for exams.
• Self-paced learning options
  • For those who prefer flexibility, Data Days will include self-paced learning opportunities on Microsoft Learn—the goal is simple: make it easy to learn on your schedule.
• Community sessions
  • Join expert-led sessions designed to help you connect with the Microsoft Fabric and data community, share best practices, and grow your technical impact.
• Dataviz World Championships
  • Experience the kickoff of the Power BI Dataviz World Championships and other global challenges that highlight creativity, technical skills, and innovation across the data and AI community.

Invest in your future

As AI continues to reshape how organizations work with data, the professionals who keep learning and adapting will be the ones leading what comes next. Data Days is designed to help you build practical skills, connect with the broader data community, and grow your expertise across Microsoft’s data and AI platform.

Whether you’re preparing for a certification, exploring new technologies, or looking to deepen your technical skills, Data Days offers hands-on learning, expert guidance, and community-driven experiences to help you move forward with confidence.

I hope you’ll join us to be part of the future of data and AI.

Register for Data Days today! The event runs June 15 through August 7. Sign up to access live training, certification prep, community challenges, and a limited number of free certification exam vouchers while supplies last.

Invest in your future with Data Days

Upskill across data, analytics, and AI with expert-led sessions, certification pathways, and flexible learning options.

Register for Data Days

The post Data, AI, and the case for continuous learning appeared first on Microsoft Fabric Blog.

This shift introduces a new constraint. The challenge is no longer model capability, but consistent, shared data context across the business.

Developers and business users know what they want to automate, and today’s models can deliver. The bottleneck is context. Every new agent starts from zero, relearning how the business works, where data lives, and what rules to follow. Without a consistent foundation, agents can’t coordinate or scale.

That’s the challenge we are solving with Microsoft Fabric. It provides a unified data and AI platform that empowers you to bring together data and move from isolated AI experiments to production-ready agent systems, in which each new agent builds on shared organizational context. This vision is already driving strong momentum among the millions of developers building on Fabric and Microsoft Databases.

Unify teams and data with Microsoft Fabric

At Microsoft Build, we are extending this foundation with new capabilities that help developers move from prototype to production faster. These include Rayfin, a new software development kit (SDK) and command-line interface (CLI) designed to make Fabric a production-ready application backend, and Azure HorizonDB, a new PostgreSQL database designed for AI‑powered applications, now in public preview.

Introducing Rayfin: From prompt to production backend

Coding agents are accelerating app development. Moving those applications from prototype to production, however, remains a challenge. Agent-created or not, every production-ready application still relies on a backend to manage data, enforce identity and permissions, coordinate state, and operate reliably over time. Existing software-service platforms were either not designed for agents or do not fully meet enterprise requirements for deployment, security, and governance.

Rayfin, a new open-source SDK and CLI, is designed to close that gap. It lets developers and coding agents describe what to build and get an enterprise-grade application backend directly into the application code, including a database, authentication, and more. Rayfin then deploys directly to Microsoft Fabric, giving every application enterprise-grade security and scale from day one. Developers and AI agents can now move from prompt to production without managing infrastructure.

With Rayfin, developers work through familiar GitHub‑based workflows to define data models, backend logic, and access policies entirely in code, giving teams and agents a consistent, programmable interface for building and managing applications. Watch Rayfin in action:

Because Rayfin can be deployed directly on Fabric, application data lands directly in OneLake, where it is immediately available to the full Fabric data stack, unified with analytics, operational and real-time data, and AI engines by default. This enables developers to build their enterprise apps on trusted business logic, integrate with semantic models, and embed rich data visuals.

We’re excited to partner with Replit, a leading AI coding platform, to help customers build enterprise-grade apps in the interface they know and love while keeping app, data, and services managed in their own Fabric tenant.

Rayfin unlocks a new development model for our users. Agents write the code. Fabric ships it quickly and safely. Together, we’re giving developers something they’ve never had before: a path from idea to enterprise-grade production that’s measured in hours, not months.

—Amjad Masad, Chief Executive Officer (CEO) of Replit

Learn more about Rayfin by reading the blog or watching the Microsoft Build session “BRK225 – Data, apps, and agents: the future of app dev with Microsoft Fabric” on Wednesday, June 3, 2026, at 1:30 PM PT.

Microsoft Databases, designed for AI applications

For decades, databases have been the backbone of enterprise applications. As applications become more intelligent and agent‑powered, we are evolving Microsoft Databases into the foundation optimized for real‑time, AI‑ready, and operationally rich experiences.

Azure HorizonDB: Enterprise-ready PostgreSQL built for the demands of AI applications

As a leading PostgreSQL committer, Microsoft has long invested in the PostgreSQL community. But as AI‑powered applications place new strains on scale, latency, and resilience, the demand for a new class of PostgreSQL database is clear.

Azure HorizonDB is that next step. Now available in public preview, HorizonDB is a fully managed, PostgreSQL‑compatible database that combines PostgreSQL familiarity with cloud‑scale architecture. It’s zone resilient by default and delivers elastic storage that scales to 128 TB, massive scale‑out compute up to 3,072 vCores, and can sustain sub‑millisecond, multi‑zone commit latency for demanding transactional scenarios.

Learn more about the Azure HorizonDB preview

As our data demands have expanded exponentially because of our use of Azure AI to chat with our data, HorizonDB has come at the perfect time to meet the performance, scale, and security we need to shift into this new world of AI-enabled data.

—Rand Morimoto, President of Convergent Computing (CCO)

Beyond scalability, we’ve also infused Azure HorizonDB with experiences designed specifically for AI applications like vector search, integrated AI model management, and direct connectivity to Microsoft Foundry and Fabric. These features provide a modern foundation for building, modernizing, and scaling AI‑powered applications with confidence. Mohsin Shafqat, Director of Software Engineering at NASDAQ, mentioned, “What stood out with HorizonDB is that it aligns closely with how we already think about the problem. Instead of stitching together multiple components, it brings transactional data, vector search, and AI capabilities into a single platform, which simplifies the architecture without forcing a complete rethink.”

Learn more in the Azure HorizonDB announcement blog and by watching the Microsoft Build session “BRK223 – From rows to reasoning: Designing databases for AI apps and agents” on Tuesday, June 2, at 2:30 PM PT.

New security and migration tooling for Azure Database for PostgreSQL

As Azure HorizonDB powers a new class of high-scale, mission‑critical applications built for AI, Azure Database for PostgreSQL remains a trusted, open‑source foundation for modernizing and operating existing PostgreSQL workloads.

Today’s updates introduce two meaningful enhancements. First is the Microsoft Defender for Cloud integration, now in preview, which delivers continuous security and compliance assessments to help teams identify misconfigurations and reduce risk. Second, we’ve released new discovery and assessment tooling to help you more confidently plan migrations to Azure Database for PostgreSQL. These tools evaluate Oracle and PostgreSQL environments and provide readiness insights, sizing guidance, and cost estimates. Learn more about this migration tooling in the Microsoft Build on-demand session “OD822 – Smarter PostgreSQL migrations to power modern, intelligent apps.”

Powering intelligent, multi‑agent systems at global scale with Azure Cosmos DB

Azure Cosmos DB is Microsoft’s AI-ready NoSQL and vector database for building responsive applications and intelligent AI experiences at any scale. OpenAI, for example, chose Azure Cosmos DB as its primary operational database “because of its automatic scaling and schema-less flexibility, allowing us to iterate quickly,” said Nick Cooper, senior technical staff member at OpenAI.

At Microsoft Build, we are focused on improving developer productivity and AI quality. The Azure Cosmos DB Linux Emulator is now generally available, enabling developers to build, test, and validate applications locally across Linux, macOS, and Windows without a cloud dependency. New AI capabilities are also now in preview, including semantic reranking, which improves search relevance using built‑in contextual understanding. In addition, a new agent memory toolkit helps developers standardize persistent memory for AI agents using Azure Cosmos DB, Azure Durable Functions, and Microsoft Foundry models. Learn more in the Microsoft Build on‑demand session “OD820 – Designing reliable multi-agent apps with Azure Cosmos DB.”

Unifying databases and Fabric on a single platform

Microsoft Databases can be centrally managed through the new Database Hub in Fabric, currently in private preview, and mirrored into OneLake, bringing operational and analytical data onto a single foundation. From there, you can use Fabric to make it trusted, contextual, and ready for AI.

Building an AI‑ready data foundation with Microsoft Fabric

In the era of AI, data is the fuel, but data alone is not enough. Equally important is how that data is understood: the definitions of customers, orders, products, revenue, and the relationships between them. Today, that understanding is fragmented across customer relationship management (CRM) and enterprise resource planning (ERP) systems, productivity tools, and spreadsheets, and too often it does not travel with the data. Organizations have long relied on people to recreate this context. But as agents take on more responsibility, this gap becomes critical. Without a shared understanding of the business, agents cannot reliably reason, coordinate, or act.

Microsoft IQ addresses this missing layer by unifying enterprise intelligence into a shared foundation built to activate AI agents. It enables consistent reasoning and enterprise-scale impact, rather than isolated interactions.

At its core, Microsoft IQ brings together four interconnected capabilities: Work IQ captures how work happens, Fabric IQ models how the business operates, Foundry IQ enables agents to discover and reuse knowledge, and the new Web IQ, announced today at Microsoft Build, adds real-time global context from the web.

Fabric IQ is central to this system, grounding AI in the live operational state of the business through shared definitions, metrics, entities, and relationships, ensuring agents act with accuracy and consistency. It provides three integrated layers of business context:

1. Unified data: OneLake unifies the organization’s data estate, spanning analytical and operational data into a single, accessible layer.
2. Business intelligence: Semantic models provide structured, governed representations of that data which organizations already rely on for trusted business metrics and analyze their business.
3. Operational intelligence: Ontologies capture operational context by defining business entities and their relationships so agents can reason in the language of the business. This context can include live signals from Fabric Real-Time Intelligence, enabling organizations and their agents to understand what is happening right now and act in time to change outcomes.

This three-tiered foundation helps ensure that every agent starts with the same understanding of the business and can apply it correctly across workflows. But Frontier organizations cannot start at the IQ layer. Building this capability requires a unified data foundation. Microsoft Fabric delivers this through four core capabilities:

1. Unifying your data estate
2. Processing and harmonizing data
3. Curating semantic meaning  
4. Empowering AI agents to act

Learn more about how Fabric can help you create an AI-ready data foundation in the Microsoft Build on-demand session “OD811 – Powering the next AI frontier with a unified data platform.”

1. Unifying your data estate with Microsoft OneLake

Most organizations struggle to see their entire data estate. It is spread across systems, duplicated in multiple places, and owned by different teams, making it difficult to know what exists, where it lives, and how it connects. Microsoft OneLake brings it together into a single, AI‑ready data lake that unifies your multi‑cloud estate and enables organization‑wide access for analytics and AI.

We are making it easier to connect existing data to OneLake without moving or duplicating it with the release of shortcuts to SharePoint and OneDrive into general availability and the ability to create shortcuts directly from Fabric Data Warehouses, now in preview. We are also adding the preview of workspace-level Azure Private Link support for mirrored data sources.

The general availability of the OneLake catalog in Microsoft Foundry

At the same time, we are making it easier to connect that data to AI. With the recent general availability of the OneLake catalog in Microsoft Foundry, you can discover trusted data, explore rich metadata, and connect it directly to AI solutions. The catalog is embedded within Foundry’s Knowledge experience, making it simple to move from data discovery to AI development in a single workflow.

Learn more about all of these OneLake announcements by watching the Microsoft Build on-demand session “OD815 – Unify your entire data estate on a single, AI-ready data lake.”

2. Process data faster with a new class of GPU-accelerated analytics

Once data is unified, the next challenge is turning it into insights quickly, reliably, and at scale. We are introducing GPU-acceleration built directly into Fabric Data Warehouse to unlock a new level of performance without adding complexity.

The research behind this innovation was recently recognized by ACM SIGMOD as the “Best Industry Paper of 2026.” This breakthrough establishes Fabric Data Warehouse as the first fully managed data warehouse to offer GPU acceleration.

By integrating NVIDIA accelerated computing, query acceleration in Fabric Data Warehouse fundamentally changes how fast queries can run. In internal benchmarking conducted in May 2026, the GPU-accelerated Fabric Data Warehouse delivered up to 7x faster performance relative to three comparable external vendors for reporting and application workloads at 64-user concurrency.

This shift reflects a broader change in how modern data systems need to operate. As Ian Buck, Vice President of Hyperscale and HPC at NVIDIA, explains, “AI applications are redefining how a data warehouse needs to perform. As AI agents reason over enterprise data, analytics systems need low-latency performance for many simultaneous users. With NVIDIA accelerated computing in Microsoft Fabric Data Warehouse, Microsoft is bringing the SQL workflows customers already use into the production AI era.”

Customers are already seeing that impact. At UNC Health, “We’re seeing up to 5x improvement in our query speeds, which allows our teams to spend less time managing performance and more time delivering meaningful insights,” said Shaun McDonald, IT Manager.

Query acceleration works automatically within Fabric, speeding up queries without requiring any query rewrites. The result is consistently low‑latency analytics that power responsive applications, interactive reporting, and agent‑driven analysis, delivering fresher insights and greater confidence in data.

Query acceleration will be available for an early access preview in July 2026. You can learn more in the GPU-accelerated analytics announcement blog and by watching the Microsoft Build on-demand session “OD813 – Powering modern data analytics in Fabric Data Warehouse.”

3. Curating semantic meaning with Fabric IQ, now generally available

Once data is prepared, the next challenge is not access but understanding. Most organizations lack a shared layer of business context, forcing every agent to relearn how the business works from fragmented data. Fabric IQ, which is now generally available, addresses this gap by giving people and agents a persistent, shared understanding of the organization that they can inherit by default, so they reason from the same foundation instead of starting from scratch.

Power BI’s industry-leading semantic models already provide structured representations of your data for trusted business intelligence, serving as an ideal foundation for training agents. Ontologies in Fabric IQ, currently in preview, build on these semantic models to incorporate operational intelligence by defining business entities, relationships, properties, rules, and actions, along with live signals from Fabric Real-Time Intelligence.

Extending Fabric IQ to Microsoft Foundry and Agent 365

Today, we are extending Fabric IQ across the agent ecosystem so this shared understanding can be used consistently across every agent and application.

Microsoft Foundry and Agent 365 

Now in preview, Ontologies are accessible directly from Microsoft Foundry as knowledge sources, bringing trusted business context into both custom and built-in agent experiences. Also in preview, Fabric IQ is now integrated with Microsoft Agent 365 as a first-party model context protocol (MCP) tool, enabling organizations to ground agents in shared meaning and ensure consistent behavior across their agent estate.

Microsoft 365 Copilot: Cowork and Copilot Chat 

Fabric IQ is also extending into Microsoft 365 Copilot, including Cowork and Copilot Chat. This enables agents to access governed Fabric data, starting with Power BI reports and semantic models, to turn insights into action. Instead of static dashboards, agents can detect changes in key metrics, generate updates, trigger follow-ups, and schedule next steps, all grounded in trusted, governed data. The result is faster, more consistent execution across the organization. These experiences are currently available customers in Frontier with a Microsoft 365 Copilot license. Join the program today.

GitHub Copilot CLI 

Using Agent Skills for Fabric, Fabric IQ tools and skills for data insights are accessible through GitHub Copilot CLI, bringing governed semantic context directly into the terminal. Now you can also query Power BI reports and semantic models from the command line, grounded in governed semantic context in Fabric IQ. Teams can ask natural language questions about usage, metrics, or customer behavior and get answers grounded in Fabric data directly within their workflow, reducing back-and-forth and accelerating data-driven decisions. 

Announcing the general availability of graph and planning in Fabric

Additionally, we’re announcing the general availability of graph in Fabric, with general availability of the planning in Fabric coming later this month. Available today, graph introduces a highly scalable, relationship-first model that connects business entities, systems, and signals so teams and agents can understand how changes propagate across the enterprise and act with full context. Planning extends this foundation by enabling organizations to create plans, budgets, forecasts, and scenario models on top of Fabric’s semantic models. Notably, planning in Fabric is not just static outputs. They can be written back into Fabric to drive execution, enabling closed-loop alignment with the same system of data and context.

Learn more about these enhancements in the Fabric IQ blog and the Build on‑demand session “OD812 – Bringing Enterprise Ontology Directly into the Developer Workflow.”

4. Empowering agents to act with operations agents and Copilot in Fabric

Enterprises are increasingly moving to multi-agent systems made up of specialized agents grounded in specific data or domain expertise. These agents can be reused across multiple systems, making it easier to scale and deliver more consistent outcomes.

Announcing the general availability of operations agents

Microsoft Fabric supports this shift with native agent capabilities, including Fabric data agents and operations agents. I’m excited to share operations agents are now generally available. These agents are designed to continuously monitor real-time data, detect patterns or anomalies, and act based on predefined business logic.

Apply agentic analytics in Power BI

In addition, we recently released open-source Agent Skills for Fabric, designed to make it easier for AI tools and agents to interact directly with Fabric. These capabilities now extend to Power BI, enabling developers and analysts to create reports using natural language or even a screenshot of the desired outcome, significantly accelerating how insights are built and shared.

Copilot in Power BI can now also modify semantic models, with built-in recommendations that improve performance and make models more AI-ready. This helps teams iterate faster and deliver insights more quickly without leaving the tools they already use.

Learn more by reading the Power BI blog or by watching the Microsoft Build on-demand session “OD817 – Agentic analytics with Power BI and Microsoft Fabric.”

Watch these announcements from Microsoft Build

If you’re interested in learning more and seeing live demos on these announcements, I encourage you to watch the Microsoft Database and Microsoft Fabric sessions at Microsoft Build, available in the Microsoft Build catalog.

The post Microsoft Build 2026: Building agentic apps with Microsoft Fabric and Microsoft Databases appeared first on Microsoft Fabric Blog.

For the first time, SQLCon joined the event, bringing the Microsoft Fabric and SQL communities together in Atlanta for an unforgettable week of learning, growing, and connecting.

More than 8,000 attendees gathered across nearly 300 sessions to explore the latest in Fabric and SQL. Some of the most valuable moments did not happen on stage. They happened through conversations and shared experiences across the community.

That is what makes FabCon special. It is not just what you learn. It is who you learn it with.

From packed sessions to impromptu discussions in the hallways, FabCon and SQLCon 2026 reflected the growing energy and momentum behind the Fabric and SQL ecosystems.

Here are some of the highlights from this year’s event.

If you haven’t already, check out Arun Ulag’s hero blog “FabCon and SQLCon 2026: Unifying databases and Fabric on a single, complete platform” for a complete look at all of our FabCon and SQLCon announcements across both Fabric and our database offerings.

A week of learning and collaboration

The week began with pre-conference workshops that allowed attendees to dive deeper into Microsoft Fabric and SQL through hands-on learning.

These sessions covered topics ranging from data engineering and real-time analytics to governance, AI, and advanced SQL scenarios. Participants worked directly with product teams and community experts to explore best practices and build new skills that they could bring back to their organizations.

For many attendees, the workshops set the tone for the entire conference. They offered not only technical depth, but also early opportunities to meet peers, exchange ideas, and start conversations that continued throughout the week.

As the main conference kicked off, keynotes and breakout sessions explored how databases, analytics, real-time data, semantic intelligence, BI, and AI are coming together on Microsoft Fabric, and how organizations are using the platform to turn insights into action faster.

The Expo Hall experience

At the center of the Expo Hall, the Microsoft booth became a natural gathering point throughout the week.

It was a place to connect, explore, and take a break between sessions. Attendees grabbed coffee served by a robot, sampled custom Fabric and SQL-themed Coca-Cola flavors dispensed from Freestyle machines, and spent time with engineers and product teams while picking up a bit of conference swag.

The mix of hands-on experiences and casual conversations made it one of the most active and engaging spaces at the event.

Nearby, the Ask the Experts area gave attendees the chance to connect directly with Microsoft engineers, product managers, and community leaders. These one-on-one discussions helped participants get guidance on everything from Fabric workloads and SQL optimization to governance, security, and AI strategy. Not to mention the wealth of partners also represented in the Expo Hall allowing attendees to engage with the expertise gathered across the ecosystem.

These moments of direct engagement often turned into some of the most valuable conversations of the week.

Competition, creativity, and hands-on challenges

FabCon wouldn’t be complete without a little friendly competition.

Throughout the week, attendees tested their skills in Fast at Fabric, a timed analytics challenge where participants worked through real-world scenarios using Microsoft Fabric. Competitors analyzed data, validated assumptions, and generated insights while climbing a live leaderboard. The experience blended learning with competition in an engaging format.

The Trivia Challenge in the Microsoft booth also kept the energy high. Attendees tested their knowledge of Fabric and SQL in a fast-paced game that mixed learning with plenty of laughs. Interactive dashboards showcased Fabric capabilities while participants competed for prizes and bragging rights.

These experiences turned technical learning into something interactive and memorable while encouraging attendees to dive deeper into the platform.

Celebrating creativity and storytelling with data

The DataViz World Championships delivered one of the most anticipated and electric moments of the week.

As the live finale of an international Power BI competition, the event brought four finalists to the stage to build visualizations in real time using a brand-new dataset. In front of a live audience, they combined creativity, technical skill, and storytelling to turn raw data into compelling insights.

By the end of the session, one finalist earned the title of 2026 Power BI DataViz World Champion, closing out the competition with one of the most memorable moments of the conference.

Community at the center of the experience

At the heart of FabCon was the Community Lounge, a welcoming space dedicated to connection and community-led experiences.

Throughout the week, the lounge hosted meetups, community theater sessions, certification guidance, and informal gatherings where attendees could exchange ideas and build relationships. It became a natural meeting point where conversations continued long after sessions ended.

The event also featured a Women in Data luncheon and a DEI luncheon, which created space for discussions around leadership, resilience, and inclusive growth within the technology community. These sessions encouraged thoughtful dialogue and helped strengthen connections among attendees from diverse backgrounds.

Together, these experiences reinforced what makes the Fabric community unique: a culture of openness, collaboration, and shared learning.

Unforgettable moments from the week

FabCon is known for creating memorable experiences, and this year delivered plenty of them. Power Hour, a fan-favorite event, brought together Microsoft product teams and community leaders for an energetic session filled with creative demos, storytelling, and unexpected surprises.

Meanwhile, FabCon TV broadcast live episodes from the Expo Hall throughout the event. Interviews with speakers, community members, and product experts captured the excitement of the conference and will continue to reach audiences through recordings shared after the event. Be sure to catch these episodes as they’re released on the Fabric YouTube channel!

To celebrate the week, attendees gathered at the world-famous Georgia Aquarium to take in the unique surroundings and connect. Conversations flowed easily between admiring the unique marine ecosystem and the next Fabric and SQL project, offering a memorable backdrop for new ideas and relationships to take shape.

Building on the energy of FabCon and SQLCon

FabCon and SQLCon 2026 highlighted the incredible momentum behind the global data community.

Over the course of the week, thousands of attendees learned new skills, built connections, and explored how Fabric and SQL technologies are shaping the future of data and AI.

Most importantly, the event celebrated the people who make this ecosystem so vibrant. The ideas, insights, and collaborations that began in Atlanta will continue long after the conference ends.

Thank you to everyone who joined us this year. We look forward to seeing what the Fabric and SQL communities build next and we’re already excited to see everyone at the next FabCon SQLCon in Spring 2027.

Explore additional Fabric resources:

• Visit the Fabric website
• Join the Fabric community
• Stay tuned in to the official Fabric YouTube channel
• Read the latest updates on the Microsoft Fabric blog

The post Highlights from FabCon and SQLCon 2026: Where databases and Fabric come together appeared first on Microsoft Fabric Blog.

Learn more about FabCon and SQLCon 2026
The excitement surrounding this event reflects the same momentum we’re seeing across our data portfolio. Just two and a half years after Microsoft Fabric reached general availability, it’s already serving more than 31,000 customers and remains the fastest-growing data platform in Microsoft’s history. Fortune 500 companies like The Coca-Cola Company are already using Fabric at scale across their organizations.

Microsoft Fabric is helping us evolve our data foundation into a more unified, AI-ready platform. Combined with Power BI and capabilities like Fabric IQ, it enables the enterprise to turn data into intelligence and act on it faster.

Shekhar Gowda, Vice President of Global Marketing Technologies at The Coca-Cola Company
Our databases are accelerating just as quickly, with SQL Server 2025 growing more than twice as fast as the previous version.

Today, we’re thrilled to share how we are bringing the power of databases and Fabric together to form a truly converged data platform—one that unifies transactional, operational, and analytical data under a single, consistent architecture. I’ll also highlight how we’ve enhanced Fabric to help you transform data into the semantic knowledge AI needs to understand your business, powered by Fabric IQ and Power BI’s industry-leading semantic model technology.

Introducing the Database Hub in Microsoft Fabric
Databases sit at the heart of the enterprise data estate—a system of record powering applications, transactions, and mission‑critical insights. Yet as organizations scale across cloud, on‑premises, and edge environments, database estates have become increasingly fragmented and isolated. As AI places even greater demands on data estates, unifying databases under a single access point and control plane has become essential.

To address this challenge, Fabric is expanding its role as the central access point for enterprise data with the Database Hub in Fabric, now available in early access. Database Hub in Fabric provides a unified database management experience that brings together databases across edge, cloud, and Fabric into a single, coherent view. Teams now have one place to explore, observe, govern, and optimize their entire database estate—including Azure SQL, Azure Cosmos DB, Azure Database for PostgreSQL, SQL Server (enabled by Azure Arc), Azure Database for MySQL, and Fabric Databases—without changing how each service is deployed.

Built for scale, the Database Hub in Fabric introduces an agent‑assisted, human-in-the loop approach to database management. With built-in observability, delegated governance, and Microsoft Copilot-powered insights, teams can deploy intelligent agents to continuously reason over estate‑wide signals and surface what changed, explain why it matters, and guide teams toward what to do next. The result is a simpler, more confident way to manage databases at scale. Over time, this model enables database estates to become more proactive, resilient, and intelligent, laying the foundation for greater autonomy, while keeping humans firmly in control of goals, boundaries, and trust.

Learn more about Database Hub in Fabric and what’s new across Databases
Bringing databases together under a single management layer is a critical step as you prepare your estates for AI at scale. But it’s not the end of the journey. The challenge shifts from where data lives to how data is understood, connected, and activated across the enterprise.

Getting your data estate ready for AI with Fabric
As organizations move from traditional applications to AI‑powered, multi‑agent systems, the advantage is shifting away from the specific model you deploy. It now lies in the intelligence and context that allow agents to understand how your business is run, the state of your business, and your institutional knowledge to help take meaningful action.

This is the challenge Microsoft IQ is designed to address. Unlike point solutions on the market today, Microsoft IQ provides an intelligence layer that delivers shared, enterprise-grade business context to every agent. That context is built from three complementary sources: productivity signals from Work IQ, institutional knowledge from Foundry IQ, and live business data from Fabric IQ.

However, like the database layer, while the IQ context layer is a critical part of a successful, and healthy AI foundation, it is not the full story. Building a complete AI-ready data foundation requires investing in four core steps:

Unifying your data estate to eliminate silos and reduce architectural complexity.
Processing and harmonizing data so it becomes AI-ready, clean, connected, and structured for both operational and analytical use.
Curating semantic meaning to give agents contextual understanding, enabling them to interpret data the way your teams already do. This is where Microsoft IQ comes into play.
Empowering AI agents to act, applying that context to automate workflows, accelerate decisions, and transform operations end‑to‑end.
Unifying your data estate with Microsoft OneLake
Every AI initiative starts with the same fundamental challenge: understanding where your data lives and how to bring it together. Microsoft OneLake was built to solve that problem by unifying data across clouds, on-premises environments, and third-party platforms into a single logical data lake without unnecessary extracting, transforming, and loading (ETL), fragmentation, or duplicated copies.

Are my agents hunting for data?

Watch the podcast
Connecting to more sources than ever before
Today, we’re expanding Mirroring in Fabric to support even more systems our customers rely on. Mirroring for SharePoint lists and Dremio are now in preview with Azure Monitor coming soon, while mirroring for Oracle and SAP Datasphere are generally available—all of which are available as part of the core mirroring capabilities. We are also introducing extended capabilities in mirroring designed to help you operationalize mirrored sources at scale, including Change Data Feed (CDF) and the ability to create views on top of mirrored data, starting with Snowflake. Extended capabilities for mirroring will be offered as a paid option.

Shortcut transformations are also now generally available, allowing data to be shaped automatically as it connects to or moves within OneLake. You can convert formats such as Excel to Delta tables, now in preview, and apply AI-powered transformations.

Additionally, we are continuing to invest in open interoperability, ensuring OneLake works seamlessly with the platforms organizations already use. We are excited to announce the ability to natively read from OneLake through Azure Databricks Unity Catalog is now in public preview. We also recently announced the general availability of our interoperability with Snowflake.

I’m also excited to share that Auger, a rapidly growing supply chain platform designed to bring intelligence and automation to global operations, has built its platform on Fabric, with all data stored natively in OneLake. This architecture enables Auger customers to seamlessly access their operations data through OneLake shortcuts within their own Fabric environments and use the full power of the platform including Power BI, Fabric data agents, and more. Learn more in my blog, co-authored with Auger Chief Executive Officer Dave Clark.

Protect your data with OneLake security, now generally available
Security and governance remain foundational to OneLake. I’m thrilled to announce OneLake security will be generally available in the coming weeks, enabling data owners to define roles, enforce row- and column-level controls, and manage permissions through a single unified model that follows the data.

To learn more about these announcements, read the OneLake blog and the Fabric Data Factory blog.

Processing and harmonizing data with Fabric analytics
AI agents are only as reliable as the data you feed them. Before data can train or ground an agent, it must be integrated, cleaned, and structured, so the agent operates from consistent, trusted information. With industry-leading engines in Fabric like Spark, T-SQL, KQL, and Analysis Services, we can equip data teams to do exactly that.

Now, we are expanding these capabilities with the introduction of Runtime 2.0 in preview, purpose-built for large-scale data computation. It incorporates Apache Spark 4.x, Delta Lake 4.x, Scala 2.13, and Azure Linux Mariner 3.0 to power advanced enterprise workloads. Materialized lake views are also now generally available, simplifying medallion architecture implementation in Spark SQL and PySpark and enabling always up-to-date pipelines with no manual orchestration. In addition, a new agentic Copilot experience in notebooks delivers deeper context awareness, reasoning over your workspace, and generating code with greater speed and precision.

For real-time scenarios, we’re launching Microsoft Fabric Maps into general availability. Maps add geospatial context to your agents and operations by turning large volumes of location-based data into interactive, real-time visual insights.

For a comprehensive overview of these announcements and much more, read the Fabric Analytics announcement blog and the Fabric Real-Time Intelligence announcement blog.

Creating semantic meaning with Fabric IQ
Preparing raw data for AI is essential. The next step is transforming that data into meaningful, unified business context. That is where Fabric IQ comes in.

Fabric IQ unifies analytical data and operational data, including telemetry, time series, graph, and geospatial data, within a shared semantic framework of business entities, relationships, properties, rules, and actions. Instead of thinking in terms of tables and schemas, your teams and agents can operate on this framework, or ontology, aligned to how the business actually runs.

Fabric IQ ontologies will soon become accessible through an MCP server in preview, enabling agents to discover, understand, and act on this semantic layer. Ontologies can also serve as context sources for maps and soon in operations agents in Fabric, extending shared business context directly into operational decision-making and execution.

We are also excited to announce planning in Fabric IQ, a new enterprise planning capability that enables organizations to create plans, budgets, forecasts, and scenario models directly on top of Fabric’s semantic models. By complementing Fabric IQ’s ontologies with integrated planning, you get a complete, contextual view of your historical, real-time, and forward planning data. This allows users and agents to quickly answer what has happened, what is happening, and what should happen all from a single source. See this in action:

Finally, we recently announced a strategic partnership with NVIDIA to power the next generation of Physical AI by integrating Real-Time Intelligence and Fabric IQ with NVIDIA Omniverse libraries. The combined platform unifies real‑time operational data, business semantics, and physical simulation to enable organizations to optimize their physical operations in scenarios like intelligent digital twins, predictive maintenance, autonomous logistics, and energy optimization.

To learn more about all of our partner announcements, read the Fabric ISV announcement blog and the planning in Fabric IQ blog.

Enhancing the underlying Fabric IQ technology
Powering much of Fabric IQ’s rich experience is a combination of Power BI’s industry-leading, rich semantic model technology and graph in Fabric, our highly scalable graph database. Already delivering insights to more than 35 million active users, semantic models provide the ideal foundation for training agents through Fabric IQ. Now, with the general availability of Direct Lake on OneLake, your tables can be read directly from OneLake with native security enforcement, richer cross-item modeling, and import-class performance without data movement or refresh.

I’m also excited to share that graph in Fabric will be generally available in the coming weeks, enabling teams to visualize and query complex relationships across customers, partners, and supply chains.

To learn more, check out the Fabric IQ announcement blog and the Power BI announcement blog.

Empowering agents to act with Fabric data and operations agents
Frontier organizations are moving beyond general-purpose assistants and instead, adopting multi-agent systems composed of specialized agents. These agents are each grounded on specific data and reusable across different systems, allowing you to deliver more accurate, accelerated, and scalable outcomes.

To support your multi-agent systems, Fabric comes with built-in agent creation capabilities with Fabric data agents and operations agents. I’m excited to share that Fabric data agents are now generally available. Fabric data agents can be thought of as virtual analysts, aligned to specific domain data to support deeper analysis and deliver insights. Operations agents complement them by monitoring real-time data, detecting patterns, and taking proactive action.

Check out a quick demo of operations agents in Fabric:

These agents can be used across Fabric or as foundational knowledge sources in leading AI tools like Microsoft Foundry, Copilot Studio or even Microsoft 365 Copilot. To learn more about our AI announcements, check out the Fabric analytics blog covering data agents and the Fabric IQ blog covering operations agents.

Building mission-critical applications with developer experiences in Fabric
Developers building the next generation of AI applications need a comprehensive, cost-effective data platform that’s already integrated with your existing tools and workflows. Today, we are expanding Fabric’s developer tooling to meet that demand.

First, Fabric Model Context Protocol (MCP) is advancing with two major milestones. Fabric local MCP is now generally available, providing an open-source local server that connects AI coding assistants such as GitHub Copilot directly to Fabric. Alongside this, we’re introducing the public preview of Fabric remote MCP, a secure, cloud‑hosted execution engine that enables AI agents and automation tools to perform authenticated actions in Fabric.

We’re also enhancing our Git integration with selective branching, allowing developers to branch out for a specific feature and pull only the items they need. You also get improved change comparisons to more easily review recent updates, and new folder relationships which show how feature workspaces connect to source workspaces.

We’re also launching two open-source projects to help teams move faster with Fabric: Agent Skills for Fabric and Fabric Jumpstart. Agent Skills for Fabric is an open-source set of purpose-built plugins that let you use natural language in the GitHub Copilot terminal to harness the full power of Microsoft Fabric. Additionally, Fabric Jumpstart is designed to help you get off the ground with detailed guidance, reference architectures, and single‑click deployments for sample datasets, notebooks, pipelines, and reports.

Finally, we are announcing that the Fabric Extensibility Toolkit (FET), an evolution of the Workload Development Kit (WDK), is now generally available. Along with this release, we are enabling support for full CI/CD, variable library, and a new management experience in the Admin portal.

Read the Fabric Platform announcement blog
Migrating your existing Azure service to Fabric
As Fabric continues to grow in functionality, we are also simplifying the migration from other Azure services. In addition to our existing Synapse tooling, we are bringing new migration assistants for Azure Data Factory, Azure Synapse Analytics, and Azure SQL in public preview.

The new Fabric migration assistant for Azure Data Factory and Synapse Analytics helps move your existing pipelines and artifacts like Spark pools and notebooks into Fabric with minimal disruption. It’s designed to support incremental modernization, allowing teams to evaluate, convert, and optimize pipelines as they transition to Fabric. The migration assistant for SQL databases helps move SQL Server into Fabric by importing schemas through DACPACs, identifying and resolving compatibility issues with AI assistance, and guiding teams through assessment and data copy workflows for a smoother cutover.

See more Fabric innovation
Explore the AI shift with The Shift podcast
In addition to the announcements above, we are also rolling out a broad set of Fabric innovations across the platform. For a deeper look at the updates and what’s new this month, visit the Fabric March 2026 Feature summary blog, the Power BI March 2026 feature summary blog, and the latest posts on the Fabric Updates channel.

Explore additional resources for Microsoft Fabric
Sign up for the Fabric free trial. View the updated Fabric Roadmap. Try the Microsoft Fabric SKU Estimator.
Visit the Fabric website. Join the Fabric community. Read other in-depth, technical blogs on the Microsoft Fabric Updates Blog.
Read additional blogs by industry-leading partners
Sonata Software: Building an AI-ready data platform with data agents, ontology, and governance in Microsoft Fabric
Quadrant Technologies LLC: Real-Time Operational Intelligence in Microsoft Fabric: Deep Dive into RTI Capabilities, Anomaly Detection and Activator Alerting
Inspark: Why switch from Azure Synapse to Microsoft Fabric?
Esri: Unlock the power of location intelligence with ArcGIS for Microsoft Fabric
Dream IT Consulting Services: 8 Real-World Use Cases of Data Agents in Microsoft Fabric
UB Technology Innovations Inc.: From Data Platform to Decision Platform: How Microsoft Fabric and Copilot are Redefining Enterprise Analytics
Simpson Associates: Fabric Data Warehouse: Bringing Structure to Modern Data Strategies
Synapx Ltd.: Migrating Power BI to Microsoft Fabric Lakehouse with Medallion Architecture: A Strategic Imperative for Modern Construction Enterprises
Cloud Services: Real-Time Intelligence in Action: How Microsoft Fabric Helped Delfi Transform Its Newsroom
Cloud Services: Microsoft Fabric Data Agents: A New Reality
iLink Digital: Detect to Act in Seconds: How Real-Time Intelligence Is Rewriting the Rules of Emissions Management
Valorem Reply: How Nonprofits Are Rethinking Data with Microsoft Fabric

The post FabCon and SQLCon 2026: Unifying databases and Fabric on a single data platform appeared first on Microsoft Fabric Blog.

This year is especially meaningful, as it marks the return of a Microsoft‑led SQL community event, while also showcasing how SQL continues to evolve as a critical part of Fabric. It is not just about new technology, but about reconnecting with each other and building the future of SQL together.

It’s inspiring to see the Microsoft SQL community continue to grow and engage, with user groups worldwide keeping conversations active across the SQL portfolio and a lot of customers using Microsoft SQL to innovate every day. With a comprehensive portfolio built on strategic common foundations and available across edge, PaaS, and SaaS, Microsoft databases form a unified platform for modern enterprise needs, whether you are migrating and modernizing, building cloud-native AI applications, or unifying your data.

Learn more about what’s happening at SQLCon
Migrate and modernize with Azure SQL
Many of our customers are not modernizing in one big leap. You are evolving from SQL Server to hybrid and then to cloud services, and you want that journey to feel familiar, predictable, and low risk. That is exactly what Azure SQL is designed to deliver. Built on a consistent Microsoft SQL foundation from on premises to the cloud, Azure SQL brings AI capabilities directly into your database experience, along with enterprise‑grade security, high availability, and the flexibility to scale as your needs grow. Azure SQL is fully SQL compatible, delivers strong performance and low latency, and supports hybrid scenarios through Azure Arc.

AI agents are becoming an important accelerator for database migration and modernization at Microsoft, helping our customers reduce manual effort and move faster with more guided experiences across the journey. The general availability of GitHub Copilot in SSMS 22 is a great example of that investment in action: you can use the same GitHub Copilot experience you already use in Visual Studio and VS Code, now inside SQL Server Management Studio (SSMS), with chat and code assistance that helps you write, edit, and refactor T‑SQL more quickly and confidently. Whether you are a developer or database administrator (DBA), new to SQL or highly experienced, GitHub Copilot can support common workflows like improving queries and assisting with troubleshooting and administration tasks right where you work, and we are continuing to expand what it can do.

Today we are announcing savings plan for databases, a flexible, spend-based pricing option that helps you save up to 35%1 vs. pay-as-you-go prices on a one-year commitment. Savings plan for databases is designed for modern, evolving database environments: Customers commit to a fixed hourly spend for one year and receive lower prices across eligible Azure database services. Savings are automatically applied to the highest-value usage each hour, helping reduce costs while supporting migration, modernization, and architectural change.

Build cloud-native AI apps at scale
Once you move to the cloud, the questions shift. How do you build faster, scale smarter, and unlock more value from your data without re‑architecting everything you have already built? That is where Azure SQL Database Hyperscale comes in.

With Azure SQL Database Hyperscale, customers gain better price-performance, elastic scale and resilience for any workload, without the cost or disruption of rewriting T‑SQL or reworking operational models. Its unique architecture, built on shared storage and multiple replicas, allows you to scale reads independently from writes. With built‑in HTAP isolation, applications can handle massive transactional and analytical workloads without complex redesign. New capabilities now in public preview extend that foundation even further, including the SQL MCP Server for securely connecting SQL data to AI agents and Copilots, as well as larger 160 and 192 vCore options for high‑throughput workloads.

We’re delivering faster, more capable vector indexes to power AI applications. Recent enhancements improve vector search performance and efficiency with no code changes required. With full insert, update, and delete support, vector indexes stay current in real time, enabling dynamic applications. Features like quantization, iterative filtering, and tighter query optimizer integration provide faster, more predictable results, helping teams build responsive AI experiences directly on their SQL data.

Temenos built its next‑generation banking platform, Temenos Core, on Azure using Azure SQL Database Hyperscale to achieve global scale, high availability, and resilient performance. The platform processes billions of transactions daily and more than 17,500 transactions per second at peak. By building on Hyperscale, Temenos reduced onboarding time, accelerated innovation, and shifted banks from worrying about downtime to competing on availability and digital innovation.

Unify your data estate with SQL database in Fabric
We continue to raise the bar on enterprise readiness for SQL database in Fabric by bringing enterprise-grade security and compliance capabilities directly into the platform. Today at SQLCon, we announced the general availability of features including SQL Auditing, Customer‑Managed Keys, and Dynamic Data Masking, and the preview of workspace‑level Private Link. We brought these enhancements to help customers meet strict governance and regulatory requirements without adding operational complexity. The result is confidence that your SQL workloads in Fabric are secure, compliant, and ready for production.

SQL database in Fabric is becoming even more powerful for AI‑driven applications. The same vector indexing enhancements available in Azure SQL Database Hyperscale are now built into SQL database in Fabric as well. Because both are powered by the same Microsoft SQL engine, customers benefit from consistent performance, capabilities, and innovation across the SQL portfolio—making it easier to build intelligent applications wherever their data lives.

Finally, moving to SQL database in Fabric is simpler than ever. The Migration Assistant now supports SQL database in Fabric as a target destination. It provides a Copilot-assisted experience that helps SQL developers assess readiness, migrate schema, identify compatibility issues, and copy data with less manual effort. By preserving familiar SQL skills and workflows, customers can modernize at their own pace while accelerating time to value on Fabric’s unified analytics and AI platform.

Learn more about SQL database in Fabric
There is one more Fabric innovation that matters deeply for how we deliver Microsoft databases as a unified platform. As applications grow more sophisticated, most organizations now rely on a mix of SQL and NoSQL databases across cloud, on‑premises, and edge environments. Provisioning, monitoring, and maintaining health across a growing database fleet often requires multiple tools and portals, making it harder to see what’s happening and manage at scale.

To address this, we are introducing the Database Hub in Microsoft Fabric, now available in early access. The Database Hub provides a unified database management experience that brings together databases across edge, cloud, and Fabric into one coherent view. From a single place, database teams can explore, observe, govern, and optimize their entire estate, including Azure SQL, Azure Cosmos DB, Azure Database for PostgreSQL, SQL Server enabled by Azure Arc, and Azure Database for MySQL without changing how each service is deployed or operated.

Built for scale, the Database Hub introduces an agent-assisted, human-in-the-loop approach to database management. Intelligent agents continuously reason over estate-wide signals to surface what changed, explain why it matters, and guide teams toward what to do next, while built-in observability, delegated governance, and Copilot-powered insights help teams move from insight to action with greater confidence. With the Database Hub, teams spend less time navigating tools and more time enabling what comes next: unlocking deeper integration across applications, analytics, and AI from a single control plane for the Microsoft databases portfolio.

Database Hub is available today in early access. Sign up today and see how the Database Hub can bring clarity and control to your database estate.

Moving forward with the SQL community
SQLCon is about bringing the SQL community together. It is about rebuilding connections and shared learning. It also reflects our long-term commitment to SQL. With a comprehensive portfolio built on strategic common foundations and available across edge, PaaS, and SaaS, Microsoft databases provide a unified platform for modern enterprise needs, whether you are migrating and modernizing, building cloud-native AI applications, or unifying your data. We are investing in SQL for the future, alongside the community that continues to shape it.

Finally, SQLCon is coming to Europe! Join the global data and SQL community from 28 Sep – 01st October, 2026 in Barcelona, Spain for hands-on learning, expert insights, and real-world stories. Register to be a part of it. I can’t wait to see you there.

Additional SQL resources
Get early access to Database Hub in Fabric
Microsoft Azure Summit: Migrate and Modernize with Agentic AI
What is new about SQL database in Fabric
Learn more about savings plan for databases
1Customers may see savings estimated to be between 0% and 35%. The 35% savings estimate is based on one Azure SQL Database serverless running for 12 months at a pay-as-you-go rate vs. a reduced rate for a 1-year savings plan. Based on Azure pricing as of March 2026. Prices are subject to change. Actual savings may vary based on location, database service, and/or usage.

The post Advancing agentic AI with Microsoft databases across a unified data estate appeared first on Microsoft Fabric Blog.

Subscribe to The Shift podcast

Today we’re introducing “The Shift” podcast, an evolution of “Leading the Shift,” to share more dialogue. Grounded in questions we heard from you after announcements at Ignite, we’re releasing eight episodes this spring—one each week—that bring engineering, product, and strategy perspectives together. Across levels and backgrounds, this season’s agentic theme explores agents up and down the stack. Knowing change is the only constant, “The Shift” creates space for us all to think out loud.

Here’s a sneak peek of the new season

Topics we’ll explore weekly
Are my agents hunting for data?
How do agents work together?
Wait, my agent needs a database?
Is context engineering the new RAG?
What senses do my agents need to act?
Is Postgres the wave of the future?
Should my IT team hire agents?
How do we draw agentic borders?
Agents don’t succeed in isolation. They depend on how your data is unified, how your cloud handles scale, how your applications orchestrate across systems, and ultimately, how this serves people. At Microsoft, we see agents as catalysts for innovation across your entire environment, performing best when layers of the stack work together. That’s where the toughest challenges for technical teams emerge: observability, governance, security, optimization, and quality. It’s a team sport.
Your data strategy determines what your agents can reason over. Your cloud foundation determines what you can do reliably. Your agents and AI app experiences deliver business outcomes. Our colleagues and friends featured on The Shift are solving for these interdependencies. And what they all have in common is conviction that none of this works in pieces.

Our first episode, “Are my agents hunting for data?” drops tomorrow. We’ll sit with Ronald Chang, Dipti Borkar, Josh Caplan, and Cillian Mitchell from the Microsoft Fabric and Microsoft OneLake teams to cover why data preparation is essential to fueling agents with knowledge. And it’s perfect timing with Microsoft Fabric Community Conference next week in Atlanta. I hope you’ll join us to keep this conversation going.

Subscribe today on YouTube, Spotify, Apple Podcasts, Amazon Music, RSS.com, or wherever you listen and learn.

The post Unpacking your top questions on agentic AI: The Shift podcast appeared first on Microsoft Fabric Blog.