Power BI is the reporting and visualization layer inside Microsoft Fabric. Fabric handles data ingestion, storage, transformation and governance; Power BI connects to what Fabric produces and turns it into dashboards and reports. They are not two products you choose between: Power BI ships as one of Fabric's workloads.

What Power BI looked like before Fabric

Before Fabric, a Power BI-based analytics stack was built from separate pieces. Power BI Desktop handled report authoring, the Power BI service handled sharing, Power Query handled data preparation, and a separate tool such as Azure Data Factory or Synapse covered anything upstream of the model. Each piece worked, but data warehousing, ETL and reporting lived in different products with their own permissions and billing.

What Fabric changed

Microsoft Fabric became generally available in November 2023, after a public preview earlier that year. It brought data integration, data engineering, data warehousing, data science, real-time analytics and Power BI into one SaaS product, billed from a shared Fabric capacity instead of separate services.

Fabric's workloads:

• Data Factory – pipelines and Dataflows Gen2 for ETL and data integration.

• Data Engineering – Spark notebooks and Lakehouses for large-scale processing.

• Data Science – machine learning and AI-driven analytics against the same data.

• Data Warehouse – a SQL-based warehouse with a T-SQL query surface.

• Real-Time Intelligence – ingesting and querying streaming data as it arrives.

• Power BI – the reporting and visualization layer on top of everything above.

All of them read and write through OneLake, a single storage layer shared across the workloads. A table a data engineer builds in a Lakehouse is the same table a Power BI report can connect to, with no export or copy step in between.

How Power BI connects to Fabric data

A typical flow: a data engineer builds a pipeline in Fabric's Data Factory that writes data into a Lakehouse or Warehouse. Analysts then connect Power BI to that Lakehouse or Warehouse and build a semantic model, measures and reports on top of it.

Power BI can read Fabric data three ways:

• Import, the same as connecting to any other source: Power BI copies the data into its own model.

• DirectQuery, querying the Fabric Warehouse or Lakehouse SQL endpoint live on every interaction.

• Direct Lake mode, unique to Fabric: Power BI reads the OneLake Delta tables directly, without a full Import copy and without DirectQuery's per-query round trip to a separate database engine. See our guide to Import versus DirectQuery for how the first two compare; Direct Lake is available only when the source is a Fabric Lakehouse or Warehouse table.

Why this matters for a Power BI team

A team already using Power BI does not need to relearn the tool to use Fabric. What changes is everything upstream of the report: pipelines, transformation and storage all move into the same workspace and the same capacity, instead of a separate Azure subscription and a separate billing relationship. Governance also moves with it: a Microsoft Purview sensitivity label applied to a Fabric item can propagate to what is built on top of it, including a Power BI report. For the fuller case for adopting Fabric, see why choose Microsoft Fabric; for how Fabric's own Data Factory compares to the standalone Azure service, see our Data Factory showdown.

FAQs

How does Microsoft Fabric change the Power BI ecosystem?

It replaces a stack of separate tools with one platform sharing a single storage layer, OneLake. Pipelines, data engineering, warehousing and Power BI reporting run in the same workspace and the same capacity, and Power BI can read Fabric tables through Direct Lake mode without a separate Import step.

What does Copilot do inside Power BI on Fabric?

Copilot in Power BI generates DAX measures and Power Query steps from a plain-language description, and writes narrative summaries of report pages. It assists someone already building or reading a report; it does not replace building the semantic model or choosing what to visualize.

Sources

• Microsoft Fabric documentation - Microsoft Learn

• Direct Lake overview - Microsoft Learn