Power BI

Accelerate app development: Cosmos DB (NoSQL) in Fabric now in preview

This removes the barriers between users and insights, enabling everyone—from business analysts to data scientists—

engage in natural language conversations with their data across multiple reports and semantic models

This chat with your data experience will allow users to ask broader questions and intelligently retrieve the most relevant data

Coming soon in public preview, Fabric data agents can be added to any custom agent built in Microsoft Copilot Studio

Once connected, the custom agent uses the Fabric data agent to retrieve insights from OneLake, respecting data access permissions

Developers can also define actions (e.g., send an email or trigger workflows) to automate processes

For teams tasked with building new AI and analytics solutions, finding and accessing the necessary data across a sea of disconnected data services

Shortcut transformations

These updates reinforce our commitment to Fabric’s four core pillars: A complete, AI-powered data platform. An open, AI-ready data lake. Empowering AI-enabled business users. A mission-critical foundation.

The general availability of the Native Execution Engine enables Spark queries to run natively on your lakehouse—up to 6x faster with no code changes or vendor lock-in. This release brings built-in optimizations and resource profiles for faster, more cost-effective data engineering at scale.

real-time endpoints for ML models

The preview of Warehouse Snapshots enables users to access a consistent view of data from a specific point in time, even during ETL processes

Copilot for SQL Analytics Endpoint in the context of your business Picture this: you need to tie customer orders from your mirrored CRM to fulfillment data in the Warehouse – something that normally requires digging through schemas, writing complex joins, and double-checking table relationships. With Copilot, you skip the heavy lifting. A simple prompt – ‘Get customer orders from CRM and join with fulfillment data from the warehouse‘ – returns a ready-to-run query that pulls exactly what you need, no manual schema deep dives required. Or maybe you’re looking to blend product metadata in a Lakehouse with sales numbers stored in a Warehouse. Instead of bouncing between storage formats and trying to reconcile differences yourself, you ask Copilot: ‘Show me top-selling products by category using product metadata from the Lakehouse and sales from the warehouse.‘ Copilot does the heavy lifting, stitching sources together behind the scenes so you can focus on the insight, not the integration. And when you’re under pressure to deliver quick insights – like pulling revenue by region for a quarterly review – Copilot has you covered there, too. Even if you’ve never touched the Finance Lakehouse, you can ask: ‘Show me total revenue by region for the last quarter using the Finance Lakehouse.‘ Copilot identifies the right tables, applies the correct filters, and generates the SQL you need without the typical back-and-forth. Copilot transforms how you work with data: no more searching, stitching, or second-guessing. Complex environments become accessible. Insights flow faster. Data silos disappear. With Copilot in SQL Analytics Endpoint, you don’t just save time, you unlock the full power of Fabric and move from question to impact without missing a beat.

Fabric Copilot and AI Capabilities available on all paid SKUs

Low-code AI tools to accelerate productivity in notebooks (Preview)

Low-code AI capabilities in Data Wrangler (Preview)

Convert natural language to code with Copilot:

Data Warehouse ALTER Table Drop Column and sp_rename column support in Fabric Warehouse (Generally Available) There are two powerful new features in Fabric Warehouse that we are happy to introduce: ALTER TABLE DROP COLUMN and SP_RENAME COLUMN. ALTER TABLE DROP COLUMN effortlessly removes unnecessary columns to streamline storage, boost performance, and improve query efficiency. Cloning a table as of a point in time & time travel to a point in time that is before the table was dropped is not supported. Dropping columns from Lakehouse tables is not a supported scenario. SP_RENAME COLUMN easily renames columns without downtime, making schema adjustments faster and reducing the risk of errors.Columns and Tables are not renamable in Lakehouse.

Migration assistant for Fabric Data Warehouse (Preview)

The Migration Assistant for Fabric Data Warehouse is now in preview. The migration experience is built natively into Fabric and enables Azure Synapse Analytics (Data Warehouse) customers to transition seamlessly to Microsoft Fabric. This new DW migration experience allows users to easily migrate both metadata and data from the source database, automatically converting the source schema to Fabric Data Warehouse, helping with data migration, and providing AI powered assistance. With integrated assessment tools and guided support, this capability simplifies migration, enabling customers to leverage Fabric’s capabilities without the complexity of traditional migrations. The Migration Assistant for Fabric Warehouse streamlines the migration process into four steps:

BULK INSERT statement (Generally Available) The BULK INSERT statement in Fabric Data Warehouse is generally available, it enables you to ingest data into a table from the specified file path:

Databases SQL database in Fabric We have several new advances to share in SQL Database within Fabric. Continuous innovation is at the heart of our development, outlined are several key enhancements.

This capability enables customers to automate, scale, integrate, and govern their SQL databases within Microsoft Fabric, using a declarative approach with Terraform. HashiCorp Terraform, an open-source tool that offers a secure, predictable, and consistent method for deploying and managing infrastructure across multiple cloud environments. This functionality extends the capabilities of Fabric through Infrastructure-as-Code (IaC).