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.

With more than 200 sessions across every Fabric workload, attendees will gain practical skills, learn about the latest product announcements, connect with like-minded community members, and gain insights directly from the Microsoft teams building the Fabric platform.

Additionally, there are over 20 full-day workshops attendees can choose to add to their program to start off the week with focused training on key areas of interest.

And for the first time, we’re thrilled to host the SQLCon conference, which will be co-located with FabCon. As Shireesh shared in his recent blog post, attendees will have the opportunity to take advantage of both conferences for the price of a single registration. Attending either conference gives you access to the very best in Fabric and SQL training all in one location.

With FabCon just around the corner, I wanted to share a few of my top picks for must-attend sessions at this year’s event:

• “Unlocking Copilot in Fabric: Administration, Governance, and Beyond!”: in this session, Dan English and Sandeep Pawar will be diving into the capabilities and utility of Copilot in Fabric, and how this AI-driven feature unlocks best practices, new enablement strategies, and enhanced opportunities for security and governance across your data estate. Learn how you can engage with Copilot in Fabric.
• “Touch your data with Real Time Intelligence”: real time Intelligence is fundamental in driving actionable data-driven insights and value. In this session, Dominick Raimato will show you the power of Real-Time Intelligence, how you can implement it in your daily workflows, and how to build your own proof of concept to help you get buy-in from your organization to roll this out in your environment. Discover how you can enter real time intelligence within Fabric.
• “Optimizing Your Power BI Data for AI”: In this session, Emily Lisa and Tori Pinheiro will show you how to prepare, manage, and optimize your Power BI data for AI-driven experiences. They’ll cover best practices and practical guidance for refining your semantic model to help Copilot deliver more meaningful insights and share early demos of upcoming capabilities that use AI to enhance and streamline semantic models. Prepare and optimize your Power BI data for AI-driven experiences.
• “Fabric IQ: Unlock Enterprise AI with a Unified Semantic Layer”: Fabric IQ exemplifies the exciting innovation taking place in Fabric. This newly released feature creates a governed, shared semantic foundation that enables your AI agents to answer richer questions. In this session delivered by Chafia Aouissi and Jomit Vaghela, you’ll learn how to extend your semantic models, connect live data sources, and enable AI agents that drive intelligent, automated decisions. See how Fabric IQ builds on existing assets.

Microsoft Fabric 2026 CoreNotes and roadmaps

You absolutely cannot miss the CoreNotes running throughout the week, which will be the place to learn about the latest roadmaps, announcements, and innovations taking place in Fabric. Featuring leading speakers like Priya Sathy, Bob Ward, Anna Hoffman, Tessa Kloster, Yitzhak Kesselman, Justyna Lucznik, yours truly, and many more, you’ll get all of the insights you need to plan your data journey in 2026 and beyond!

Take a look at the FabCon agenda to see the full list of speakers and sessions featured at this year’s conference.

Connect with the community that’s building the future

One of my favorite parts of attending FabCon is seeing community members connecting with one another. This event brings together Microsoft product teams, MVPs, practitioners, community leaders, partners and solution builders, and new data professionals who all share the common goal of solving real-world challenges and helping each other troubleshoot, learn, and grow in their careers.

Whether you’re attending a session, joining a hallway conversation, or connecting at a networking event, FabCon is where your ideas become reality.

The return of FabCon TV

I’m excited to share that FabCon TV will be taking place once again at FabCon Atlanta. We had a lot of fun adding this experience to the conference in Vienna and we look forward to sharing it with you all in March. We have lots of fun segments in store!

Check out my FabCon TV segment with host Patrick LeBlanc from FabCon Vienna in September:

Save your seat for FabCon and join the action

I’m excited to share that FabCon TV will be taking place once again at FabCon Atlanta. We had a lot of fun adding this experience to the conference in Vienna and we look forward to sharing it with you all in March. We have lots of fun segments in store!

Check out my FabCon TV segment with host Patrick LeBlanc from FabCon Vienna in September:

See you in Atlanta!

The post Top sessions you won’t want to miss at the Microsoft Fabric Community Conference 2026 appeared first on Microsoft Fabric Blog.

Register once for unrestricted access to both events, allowing you to select the content that best meets your learning needs. If you’re a data professional looking to learn more about migrating and deploying powerful data platform solutions, or you’re a SQL pro who wants to stay ahead of innovations in SQL databases, SQL in Fabric, Azure SQL, and more, FabCon and SQLCon is your must-attend event in 2026.

FabCon and SQLCon will be one of the year’s largest gatherings of data professionals from around the world, bringing together tech enthusiasts, innovators, and industry leaders to explore the future of data, SQL, analytics, business intelligence, and AI integration.

Workshops, keynotes, sessions, and demos will take deep dives into the leading-edge developments within the worlds of Microsoft Fabric and databases, giving attendees a first look at product roadmaps and announcements, as well as an opportunity to connect first-hand with the teams building these solutions. There will also be informal networking opportunities throughout the week so you can share insights and make lasting connections with like-minded peers.

Keynotes and sessions with top experts and new features

Keynote speakers feature top Microsoft leaders and engineers from across the data and SQL universe including yours truly, Arun Ulag, Amir Netz, Wangui McKelvey, Nellie Gustafsson, Justyna Lucznik, Patrick LeBlanc and Adam Saxton (AKA Guy in a Cube), Shireesh Thota, Priya Sathy, Erin Stellato, Bob Ward, and Anna Hoffman to name just a few. These keynotes will give attendees a first look at the latest announcements, features, and updates in Fabric and databases, and show you how to implement them in your real-world scenarios.

I’m also thrilled to share that FabCon and SQLCon sessions have just been announced! Our diverse lineup of speakers and content covers the spectrum of use cases, challenges, fundamentals, and in-depth training for attendees of all levels—and, with the help of these expert sessions, you can start implementing new features immediately. Some of the topics I’m really excited about are:

• Monitor and Troubleshoot Your Data Solution in Microsoft Fabric with Li Liu and Haydn Richardson—explore best practices and new capabilities for consistent and reliable performance in your data solution.
• Empowering Fabric Administrators: Securing, Scaling, and Sustaining Your Data Estate with Arthi Ramasubramanian Iyer and Adi Regev—take a strategic look at how you can build confidence, clarity, and resilience across your Fabric estate to protect data at scale.
• From Reactive to Proactive: Solving SQL Performance Issues with Agentic AI: Learn how to implement agentic AI to detect regressions, analyze queries, find indexing gaps, and provide instant fixes.
• A Guide to Making the Most of Your SQL Skills Using Microsoft Fabric: Find out why, for many tasks, SQL is not only compatible, but often the most efficient way to build modern, scalable, and intelligent data solutions in Fabric.

Want the perfect gift? Get a FabCon and SQLCon discount!

I can’t wait to welcome you all to the first-ever combined FabCon and SQLCon event and see this conference expand to support professionals from across the world of data, analytics, and AI.

As we approach the holiday season, this is a great chance to treat yourself or a colleague to a gift they’ll love! FabCon and SQLCon features the content, training, and networking that will help attendees grow in their professional careers and make an immediate impact in their organization.

I also want to share an exclusive offer—register now before pricing increases later this month and receive an additional $200 off the price of admission with the discount code: FABHOLIDAY. This is your last chance to get locked in at these lower ticket prices!

Reminder: registration for either event gives you full access to both.

If you need help convincing your boss why this would make the perfect holiday gift, use our FabCon and SQLCon email templates to make the case.

The post FabCon and SQLCon: From workshops and keynotes to demos and deep dives appeared first on Microsoft Fabric Blog.