PL 300 Syllabus: Every Domain and Objective

Exam PL-300: Microsoft Power BI Data Analyst is part of Microsoft Certified: Power BI Data Analyst Associate. Microsoft states skills measured as of April 20, 2026, and the certification remains active with no retirement banner shown. This pl 300 syllabus reflects that published skills-measured document, organized by domain and objective statement.

How the PL-300 syllabus is weighted

Microsoft groups the pl-300 exam objectives into three domains, each carrying a percentage of the overall score.

The two largest domains, data preparation and visualization, sit at the same weight, so neither can be skipped in favor of the other. Manage and secure Power BI carries the smallest share but still touches workspace governance topics that show up across several questions.

Domain 1: Prepare the data (38%)

This domain covers connecting to sources, cleaning the data, and shaping it for the model. The pl 300 exam topics under this domain include:

• Get or connect to data - Identify and connect to data sources or a shared semantic model
• Get or connect to data - Change data source settings, including credentials and privacy levels
• Get or connect to data - Choose between DirectLake, DirectQuery, and Import
• Get or connect to data - Create and modify parameters
• Profile and clean the data - Evaluate data, including data statistics and column properties
• Profile and clean the data - Resolve inconsistencies, unexpected or null values, and data quality issues
• Profile and clean the data - Resolve data import errors
• Transform and load the data - Select appropriate column data types
• Transform and load the data - Create and transform columns
• Transform and load the data - Group and aggregate rows
• Transform and load the data - Pivot, unpivot, and transpose data
• Transform and load the data - Convert semi-structured data to a table
• Transform and load the data - Create fact tables and dimension tables
• Transform and load the data - Identify when to use reference or duplicate queries and the resulting impact

In practice, this means Power Query fluency: shaping raw tables, choosing storage modes, and building a model-ready dataset before any report work starts.

Domain 2: Visualize and analyze the data (38%)

This is the report-building and DAX-analysis domain, and it carries the same weight as data preparation:

• Create reports - Select an appropriate visual
• Create reports - Format and configure visuals
• Create reports - Create a narrative visual with Copilot
• Create reports - Apply and customize a theme
• Create reports - Apply conditional formatting
• Create reports - Apply slicing and filtering
• Create reports - Use Copilot to create a new report page
• Create reports - Use Copilot to suggest content for a new report page
• Create reports - Configure the report page
• Create reports - Choose when to use a paginated report
• Create reports - Create visual calculations by using DAX
• Enhance reports for usability and storytelling - Configure bookmarks
• Enhance reports for usability and storytelling - Create custom tooltips
• Enhance reports for usability and storytelling - Edit and configure interactions between visuals

Expect questions on choosing the right visual for a scenario, wiring up bookmarks and tooltips, and writing DAX for visual calculations rather than only model measures.

Domain 3: Manage and secure Power BI (24%)

The smallest domain still spans two distinct skill areas: workspace administration and access control.

• Create and manage workspaces and assets - Create and configure a workspace
• Create and manage workspaces and assets - Configure and update an app
• Create and manage workspaces and assets - Publish, import, or update items in a workspace
• Create and manage workspaces and assets - Create dashboards
• Create and manage workspaces and assets - Choose a distribution method
• Create and manage workspaces and assets - Configure subscriptions and data alerts
• Create and manage workspaces and assets - Promote or certify Power BI content
• Create and manage workspaces and assets - Identify when a gateway is required
• Create and manage workspaces and assets - Configure a semantic model scheduled refresh
• Secure and govern Power BI items - Assign workspace roles
• Secure and govern Power BI items - Configure item-level access
• Secure and govern Power BI items - Configure access to semantic models
• Secure and govern Power BI items - Implement row-level security roles
• Secure and govern Power BI items - Configure row-level security group membership

Row-level security and workspace roles are the parts of this domain that trip up analysts who have never had to administer a workspace, so treat them as their own study block rather than an afterthought.

Prerequisites and who this syllabus assumes you already know

Microsoft states no formal prerequisite for PL-300, but the study guide recommends proficiency with Power Query and Data Analysis Expressions (DAX), plus experience preparing, modeling, visualizing, analyzing, and managing and securing data in Power BI. If any domain above looks unfamiliar rather than just rusty, read our PL-300 prerequisites page before you commit to a date.

Turning this syllabus into a study plan

A syllabus tells you what to cover, not how to sequence it. Our PL-300 study plan breaks these same three domains into week-by-week blocks, weighted the same way Microsoft weights the exam. Once you have worked through a domain, check your recall against our PL-300 sample questions, which are labeled by the domain they test.

For everything outside the syllabus itself, including duration, passing score, and question format, see the PL-300 exam format and scoring page, and for how to book, see PL-300 cost and booking.

Exam facts on this page come from Microsoft’s own pages (official exam page). Prices, versions and policies change — confirm there before you book.