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Download PDFHow to Pass the PL-300 Power BI Certification
Learn how to pass the PL-300 certification exam for Power BI—one of the world's most popular business intelligence tools—in this convenient cheat sheet!
Overview
What is the PL-300 Certification?
PL-300 is a professional certification in Microsoft Power BI for people working as (or wishing to work as) a data analyst or business analyst. The exam tests you in four areas:
- 25% to 30% Preparing data
- 25% to 30% Modeling data
- 25% to 30% Visualizing and analyzing data
- 15% to 20% Managing and securing Power BI
Skills as measured from 20 April 2026. A score of 700 or higher passes, and the credential renews each year through a free assessment on Microsoft Learn.
How to use this cheat sheet
All the skills you need to pass PL-300 are listed here. If you are just considering taking the exam, read through the skills to see what you'll be working on.
If you are already working toward PL-300, find skills that you want to work on, then look up the content you need to take to gain those skills.
Prepare the Data
Preparing data means importing, cleaning, and manipulating data to get it ready for analysis.
Get or connect to data
Power BI connects to over 100 data sources, from spreadsheets to databases to web pages. You need to know how to get data from the source into Power BI.
- Identify and connect to data sources or a shared semantic model
- Change data source settings, including credentials and privacy levels
- Choose between Direct Lake, DirectQuery, and Import
- Create and modify parameters
Profile and clean the data
Datasets are seldom clean when you get them. You need to know how to detect and rectify issues with data.
- Evaluate data, including data statistics and column properties
- Resolve inconsistencies, unexpected or null values, and data quality issues
- Resolve data import errors
Transform and load the data
Even clean data often needs manipulating into a form suitable for analysis — new columns from existing ones, a subset of the rows, or tables combined.
- Select appropriate column data types
- Create and transform columns
- Group and aggregate rows
- Pivot, unpivot, and transpose data
- Convert semi-structured data to a table
- Create fact tables and dimension tables
- Identify when to use reference or duplicate queries and the resulting impact
- Merge and append queries
- Identify and create appropriate keys for relationships
- Configure data loading for queries
Model the Data
Data modeling is about defining what goes into each table and how the tables are related. (Not to be confused with statistical modeling, which is about inference and predictions.)
Design and implement a data model
The first step in data modeling is specifying the structure of each table and how the tables relate.
- Configure table and column properties
- Implement role-playing dimensions
- Define a relationship's cardinality and cross-filter direction
- Create a common date table
- Identify use cases for calculated columns and calculated tables
Create model calculations by using DAX
The ability to perform useful analytics hinges on the ability to create useful measures from the data. Power BI has an entire programming language to help you: DAX.
- Create single aggregation measures
- Use the
CALCULATEfunction to manipulate filters - Implement time intelligence measures
- Use basic statistical functions
- Create semi-additive measures
- Create a measure by using quick measures
- Create calculated tables or columns
- Create calculation groups
Example DAX Calculation:
Sales EU = CALCULATE( SUM(Sales[Amount]), Region[Continent] = "Europe" )
Optimize model performance
If a dashboard or report runs slowly, you may need to change the data or the calculations to improve the speed.
- Improve performance by identifying and removing unnecessary rows and columns
- Identify poorly performing measures, relationships, and visuals by using Performance Analyzer and DAX query view
- Improve performance by reducing granularity
Become a Power BI Data Analyst
Master the world's most popular business intelligence tool.
Visualize and Analyze the Data
Data visualization and crunching numbers are the heart of data analysis. Once you have answers, the results need to be organized into a report for consumption.
Create reports
At a basic level, you create the text, metrics, and visualizations, then arrange them in a suitable order.
- Select an appropriate visual
- Format and configure visuals
- Create a narrative visual with Copilot
- Apply and customize a theme
- Apply conditional formatting
- Apply slicing and filtering
- Use Copilot to create a new report page, and to suggest content for it
- Configure the report page
- Choose when to use a paginated report
- Create visual calculations by using DAX
Enhance reports for usability and storytelling
A report's effectiveness is largely about how many useful and interesting thoughts its users have after seeing it.
- Configure bookmarks
- Create custom tooltips
- Edit and configure interactions between visuals
- Configure navigation for a report
- Apply sorting to visuals
- Configure sync slicers
- Group and layer visuals by using the Selection pane
- Configure drillthrough navigation, including pages, filters, and buttons
- Configure export settings
- Design reports for mobile devices
- Enable personalization in a report, including personalized visuals
- Design and configure Power BI reports for accessibility
- Configure automatic page refresh
Identify patterns and trends
Beyond descriptive statistics, analysis involves many techniques to answer questions with data, from finding related data points with cluster analysis to making predictions with forecasting.
- Use the Analyze feature in Power BI
- Use grouping, binning, and clustering
- Use AI visuals
- Use reference lines, error bars, and forecasting
- Detect outliers and anomalies
- Use Copilot to summarize the underlying semantic model
Manage and Secure Power BI
Once you have your report, you need to make it available to your users, keep it up to date, and control who can see what.
Create and manage workspaces and assets
Power BI workspaces let you manage reports, dashboards, and semantic models; scheduled refresh keeps the data current.
- Create and configure a workspace
- Configure and update an app
- Publish, import, or update items in a workspace
- Create dashboards
- Choose a distribution method
- Configure subscriptions and data alerts
- Promote or certify Power BI content
- Identify when a gateway is required
- Configure a semantic model scheduled refresh
Secure and govern Power BI items
- Assign workspace roles
- Configure item-level access
- Configure access to semantic models
- Implement row-level security roles
- Configure row-level security group membership
- Apply sensitivity labels
Pass the PL-300 Certification with DataCamp
DataCamp's Data Analyst in Power BI career track takes you from zero to certification-ready. It consists of 17 courses covering content related to the skills tested by PL-300. The average completion time is around 50 hours, and completing it gets you a 50% discount code on the PL-300!
Prepare for the PL-300 with Courses
Start here
Data preparation
Data modeling
DAX calculations
Visualization and reporting
- Data Visualization in Power BI
- User-Oriented Design in Power BI
- Reports in Power BI
- Report Design in Power BI
Analysis
Deployment
Apply Your Skills With Case Studies
To make sure that you have mastered the Power BI skills needed for the exam, take these case study courses:
- Case Study: Analyzing Customer Churn in Power BI
- Case Study: Analyzing Job Market Data in Power BI
- Case Study: HR Analytics in Power BI
- Case Study: Competitor Sales Analysis in Power BI
- Case Study: Inventory Analysis in Power BI
Use Cheat Sheets to Refer Back to What You Learned
Schedule Your PL-300 Exam
Once you feel ready, redeem your discount code and schedule your exam via the Microsoft certification page.
