Microsoft Power BI Data Analyst Associate (PL-300) Cert Prep by Microsoft Press

6h 27mIntermediate2026-06-11

Authors

Microsoft Press

Microsoft

Course details

Embark on a journey to become proficient in Microsoft Power BI while preparing for certification. Begin by exploring techniques for data preparation, learning to connect to data sources, clean data, transform data, and build efficient models. Review how to create robust data models by configuring properties, implementing relationships, and using DAX calculations for insightful analysis. Visualize and analyze your data with advanced reporting features, using tools for storytelling and identifying trends and patterns. Enhance your reports with compelling visuals, interactive elements like bookmarks and drill-through features, and accessibility for all users. Learn how to manage and secure your Power BI environment effectively by reviewing how to deploy, share, and protect your data assets. This course is ideal for data professionals working closely with Power BI to deliver actionable insights through self-service analytics and for anyone who has expertise in data domains aiming to provide business value through comprehensive visualizations.

Concepts

Introduction

Exam PL-300 Microsoft Power BI Data Analyst - Introduction

Get or Connect to Data

Module 1 - Prepare the data introduction
Learning objectives
Identify and connect to data sources or a shared semantic model
Change data source settings, including credentials and privacy levels
Choose between DirectQuery and Import
Create and modify parameters

Profile and Clean the Data

Learning objectives
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

Learning objectives
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

Design and Implement a Data Model

Module 2 - Model the data introduction
Learning objectives
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

Learning objectives
Create single aggregation measures
Use the CALCULATE function
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

Optimize Model Performance

Learning objectives
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

Create Reports

Module 3 - Visualize and analyze the data introduction
Learning objectives
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
Use Copilot to suggest content for a new report page
Configure the report page
Choose when to use a paginated report
Create visual calculations by using DAX

Enhance Reports for Usability and Storytelling

Learning objectives
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 drill through navigation
Configure export settings
Design reports for mobile devices
Enable personalized visuals in a report
Design and configure Power BI reports for accessibility
Configure automatic page refresh

Identify Patterns and Trends

Learning objectives
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

Create and Manage Workspaces and Assets

Module 4 - Manage and secure Power BI introduction
Learning objectives
Create and configure a workspace
Configure and update a workspace 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

Learning objectives
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

Summary

Exam PL-300 Microsoft Power BI Data Analyst - Summary