Power BI

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).

Two flavors of Direct Lake: Direct Lake on SQL endpoint is the “legacy” version of Direct Lake

Direct Lake on OneLake is a new mode that will be integrated with OneLake security.

model in Direct Lake is always stored on the cloud, and it does not store anything on the local computer. However, this integration opens up the possibility of using external tools and simplifies the introduction of other features, like the next one.

Composite models with Direct Lake and Import mode

you can mix tables in Direct Lake mode (also coming from different sources) and in Import mode.

does not create “limited” relationships between tables from different data sources

The table in Import mode does not have the current limitations of tables in Direct Lake

ill be possible to materialize a view on Lakehouse using SQL statements

: It will also be possible to create calculated tables and calculated columns based on tables connected through Direct Lake.

The semantic model will introduce the notion of “Calendars

The last announcement is the more important one for the long term. You will be able to write and use functions defined in DAX. These are called User-Defined Functions (UDFs), which you should not confuse with User Data Functions in Azure: the DAX UDFs exist in semantic models, are written, and can be consumed in DAX.