Accelerating data and AI on Azure
Thousands of data professionals are gathering in Atlanta this week Microsoft Fabric Community Conference (Fabcon) 2026 – co-located with SQLCon For the first time ever – bringing together the Microsoft Data and SQL communities to explore the future of analytics, BI and AI on Azure.
For Azure Databricks, FabCon highlights the continued momentum of our partnership with Microsoft and how customers are using Azure Databricks to integrate data engineering, analytics, BI, and AI.
Since 2017, Azure Databricks has been a first-party Azure service that is deeply integrated with Microsoft services, including Power BI, Excel, Microsoft Teams, Data Factory, Azure OpenAI, Microsoft Foundry, Copilot Studio, and Power Platform.
Enterprises across all industries rely on Azure Databricks to build modern data platforms on the Open Lakehouse architecture, combining the flexibility of open data with the performance and scale needed for analytics and AI.
This week at FabCon, we’re introducing several new capabilities designed to make it even easier to build intelligent applications on Azure.
Lakeflow Connect Free Tier
Reliable data ingestion is the foundation of modern analytics and AI.
Today, we are excited to introduce Lakeflow Connect Free Tier So organizations can easily bring their enterprise data into their lakehouse to build analytics and AI applications.
Lakeflow Connect lets you mirror data from enterprise SaaS applications and databases directly into Lakehouse. Each scope includes 100 free dBu per dayallows you to swallow almost 100 million records per workstation, per day Admission to the Lakehouse at no charge before standard Lakeflow Connect pricing applies. This free tier includes all the benefits of Lakeflow Connect, including a simple UI, efficient ingest, and integrated governance through the Unity Catalog.
Key capabilities include:
- Database mirroring for the nine most commonly used databases (SQL Server, Oracle, Teradata, PostgreSQL, MySQL, Snowflake, Redshift, Synapse and BigQuery)
- Full support for many of the most popular SaaS applications (Including Dynamics 365, Salesforce, ServiceNow, Workday, and Google Analytics)
Lakeflow Connect writes directly Open Storage on Azure Data Lake Storage (ADLS)Governed by Unity Catalog. Your captured data is secure, searchable, and accessible as soon as it lands on any engine.
Combined with Lakeflow’s orchestration and transformation capabilities, Azure Databricks provides a complete platform for building production data pipelines – enabling teams to build pipelines. Up to 25x faster while reducing ETL costs by up to 83%.
Learn more about how Lakeflow on Azure Databricks Unifies ingestion, transformation, and orchestration on a single governed platform.
Azure Databricks Lakebase: Database for AI agents, now generally available
Modern applications require increasingly operational databases that seamlessly integrate with analytics and AI. In the age of AI agents, this is even more important: Agents need a transactional system of record to manage status, tasks, and application workflows.
Azure Databricks LakebaseNow generally available, is a managed, serverless Postgres service that brings production-grade operational capabilities directly into your Lakehouse Foundation on Azure. Lakebase is the operational database of the agentive era Which enables AI agents and applications to read, write, and reason about operational data directly in Lakehouse.
LakeBase combines the familiar Postgres with the scalability and economics of open LakeHouse storage. As organizations adopt agentic workflows powered by tools like Genie and Agent Bricks, Lakebase provides the operational database layer that agents rely on to manage state and application workflow. The foundation also enables a new wave of agentic data engineering and agentic data science with tools like Genie Code.
Key capabilities include:
- Open Postgres Foundation With community extension support like PGVector and PostGIS
- separate calculation and storage Enabling high throughput and efficient scaling
- Sub-second startup with autoscaling and scale-to-zero pricing
- Branching and quick restore for development workflow
- High availability with automatic failover In availability areas
With this launch, Lakebase is now available 14 Azure regions worldwideEnabling organizations to run operational workloads directly on the Databricks platform.
Common use cases include:
- Operational Applications and Workflow Systems
- AI agent state management
- Customer Personalization and Convenience Service
- Transactional analytics on operational data
Extending Azure Databricks to Microsoft 365
Many business decisions still take place in familiar tools such as Excel and Teams. The main focus of this week’s announcements is expanding Azure Databricks into Microsoft 365 to make governed data and AI insights available where users already work.
This builds on previously announced integration between Azure Databricks and Microsoft 365, including support for Genie-enabled CoPilot Studio agents – allowing employees to get trusted insights from Genie directly in Teams or M365 CoPilot – as well as upcoming initiatives like the Databricks app in Teams that enables direct access to Genie.
Azure Databricks Excel Add-in (Public Preview)
Azure Databricks Excel Add-in Connects Excel directly to Governed Lakehouse data.
Users can:
- browse Unity Catalog Tables and Metric Views directly from excel
- Create a pivot table using Metric views and governed semantic definitions
- Filter and analyze data without writing SQL
Works across add-ins Excel for Windows, macOS, and WebHelping organizations replace fragile exports with direct access to trusted Lakehouse data.
To know more, review this Documentation.
Genie: AI that knows your business
Adoption of AI-powered analytics on Azure Databricks has grown rapidly, with 98% of Databricks SQL Warehouse customers using AI/BI, and Genie’s monthly active users growing more than 300% year-over-year.
At the center of this experience is Genie, which enables users to ask questions about their data and receive answers in the form of tables, charts, or natural-language explanations.
Genie Databricks features conversational AI experiences for data, while Genie Code extends these capabilities to developers building pipelines, ML models, BI dashboards, and applications.
genie agent mode
For complex analytical questions, genie agent mode Introduces an agentic approach to business analysis.
uses agent mode Multi-Step Reasoning and Hypothesis Testing Investigating complex questions and uncovering deep insights from enterprise data. Instead of returning a single query result, Genie can iteratively explore a problem and refine its approach by learning from intermediate results. Genie Agent mode enables users to go beyond basic “what happened” questions to understand “why” and “what’s next.”
With Genie Agent Mode, users can:
- Automatically prepare and execute a research plan for multiple questions
- Test hypotheses and refine analysis based on intermediate findings
- Combine structured data exploration with descriptive explanations and visualizations
- Provide comprehensive answers supported by tables, charts and evidence
It replaces Genie with a simple interactive query interface. AI analyst is capable of investigating complex business problems.
genie code
For data practitioners, genie code Databricks enables agentic data engineering, data science, and analytics workflows directly in the workspace.
Genie Code is an AI agent built specifically for data teams. It understands the enterprise data context unity catalogue, It enables reasoning about datasets, lineage, governance policies and business semantics while working directly inside notebooks, SQL editors and Lakeflow pipelines.
Genie Code provides an integrated agent development experience for building and running data pipelines, analytics, and AI applications.
With Genie Code, teams can:
- Build and extend data pipelines, dashboards, and ML workflows from natural language signals
- Debug failures and investigate inconsistencies in Lakeflow pipelines and models
- Generate notebooks, SQL queries and visualizations based in an enterprise data context
- Automate routine operational tasks like pipeline monitoring and troubleshooting
By combining deep platform integration with multi-step reasoning, Genie Code allows data teams to move beyond assisted coding Handing over complex data tasks to an AI partner.
Genie in Databricks One
Databricks One now includes An integrated, multi-agent chat experience powered by GenieProvides business users with an easy way to query their entire data estate. Users can seamlessly access and combine insights from multiple Genie locations without needing to know where data resides or which location to choose. When a question goes beyond the existing Genie space, Databricks One can engage additional agents to explore the data and generate new answers. This allows users to handle both well-defined and on-the-fly queries in a single experience.
As well as chat, users can search, explore AI/BI dashboards and interact with Databricks apps within a streamlined interface designed to make data and AI accessible to everyone.
Databricks One Mobile
Databricks One Mobile brings the new Genie multi-agent chat experience to iOS and Android, enabling business users to securely access and interact with their data from anywhere.
With Databricks One Mobile, users can ask Genie questions, explore AI/BI dashboards, and access Databricks apps from their phone. It gives business users an easy way to analyze data and make decisions on the go.
Why Azure Databricks is the best data and AI platform on Azure
These announcements build on the core strengths that make Azure Databricks the platform of choice for data and AI on Azure.
unified governance
Unity centralizes catalog governance across tables, files, models, dashboards, and AI assets.
Deep Microsoft integration
Azure Databricks integrates natively with Power BI, Excel, Teams, Azure OpenAI, and other Microsoft services.
Lakehouse-Native Analytics
Databricks SQL provides high-performance analytics directly on Open Lakehouse storage.
AI development
Genie and Agent Bricks provide a unified platform for building and deploying AI applications.
Low Total Cost of Ownership
Serverless compute, Lakebase scale-to-zero, and simplified ingestion reduce infrastructure complexity and cost.
Check out these innovations at FabCon
If you are participating FabCon 2026 in AtlantaStick around to see these innovations in action. The Databricks team will be on site throughout the week demonstrating how organizations are building modern data and AI applications with Azure Databricks. you can do it too join our session Accelerating data and AI with Azure Databricks (Thursday, March 19, 8:00-9:00 am, Room C302) To see how these capabilities come together to accelerate performance, simplify architecture, and maximize value on Azure.
- At FabCon, you can:
See live demos of Azure Databricks Lakebase, Lakeflow Connect, Genie, AI/BI, and more. - Join Databricks SMEs to discuss how to integrate data engineering, BI, and AI on Azure
- Learn how customers are integrating Azure Databricks, Power BI, and Azure OpenAI
We’ll also connect with partners across the Microsoft ecosystem for community events during conference week. Join us and Slalom for a FabCon Networking Happy Hour on Wednesday 3/18 to connect with data leaders and practitioners in the Microsoft and Databricks communities:
FabCon Happy Hour with Slalom → https://go.slalom.com/MSFT-FabCon26
And mark your calendars for the Databricks Data + AI Summit, June 15-18, 2026 in San Francisco – the world’s largest conference dedicated to data, analytics, and AI, featuring Over 25,000 attendees, over 800 sessions and hands-on training on the Databricks platform.
The future of data and AI on Azure is here – and we’re just getting started!
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