Microsoft Power BI Data AnalystStudy guide
The associate certification for a Power BI data analyst who prepares, models, visualizes/analyzes, manages, and secures data using Power Query and DAX (PL-300).
About Microsoft Power BI Data Analyst (PL-300)
Microsoft Power BI Data Analyst (PL-300) is a Associate-level certification from Microsoft. This page organizes the exam scope into a 5-chapter, 13-section study guide and lets you check your understanding with exam-style practice questions. A good flow is to read the chapters below in order, then test yourself via "Practice questions."
Exam domains (approximate weighting)
- Prepare the data~27%
- Model the data~27%
- Visualize and analyze the data~28%
- Manage and secure Power BI~18%
Weights are approximate guidance for the live exam. Each domain is covered in detail in the chapters and sections below.
Official exam information: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/pl-300
1Prepare the data
- 1.1Get and connect to data
Understand connecting to data sources and shared semantic models, choosing storage mode (Import / DirectQuery / DirectLake), credentials/privacy levels, and using parameters.
- 1.2Profile and clean the data
Understand evaluating data with data profiling (column quality/distribution/statistics) and resolving inconsistencies, nulls, error values, and import errors in Power Query.
- 1.3Transform and load the data
Understand column types/creation, grouping/aggregation, pivot/unpivot, building fact/dimension tables, reference vs duplicate, merge vs append, relationship keys, and query load configuration.
2Model the data
- 2.1Design a data model
Understand star schema, table/column properties, role-playing dimensions, relationship cardinality and cross-filter direction, a common date table, and calculated columns/tables.
- 2.2Create calculations with DAX
Understand measures vs calculated columns, aggregation measures, CALCULATE, time intelligence, statistical/semi-additive, quick measures, and calculation groups.
- 2.3Optimize model performance
Understand optimizing the model by removing unnecessary rows/columns, identifying slow elements with Performance Analyzer and DAX query view, and reducing granularity.
3Create reports
- 3.1Create visuals and reports
Understand choosing the right visual, formatting and themes, conditional formatting, slicing/filtering (visual/page/report/drillthrough), and visual calculations.
- 3.2Advanced report features (Copilot and paginated)
Understand Copilot-driven narratives/report pages and model summaries, paginated vs interactive reports, and configuring report pages.
4Enhance and analyze
- 4.1Usability and storytelling
Understand bookmarks, custom tooltips, visual interactions, navigation, sync slicers, the selection pane, drillthrough, export, and mobile layouts.
- 4.2Accessibility and personalization
Understand accessibility design (alt text/tab order/contrast), report personalization, and automatic page refresh.
- 4.3Identify patterns and trends
Understand the Analyze feature, grouping/binning/clustering, AI visuals (key influencers/decomposition tree), reference lines/forecasting, anomaly detection, and Copilot summaries.
5Manage and secure Power BI
- 5.1Manage workspaces and assets
Understand workspaces and apps, publishing and distribution, dashboards, subscriptions/alerts, promotion/certification, gateways, and scheduled refresh.
- 5.2Security and governance
Understand workspace roles, item-level access, semantic model Build permission, row-level security (RLS), and sensitivity labels.