Exam PL-300 Microsoft Power BI Data Analyst (Video), 4th Edition, 4th Edition

Description

Fully Updated! Prepare for Microsoft Exam PL-300 and level up in your career as a Power BI Data Analyst

This Exam PL-300 Microsoft Power BI Data Analyst video is designed for data analysts responsible for designing scalable data models, cleaning and transforming data, and presenting analytic insights through data visualizations using Power BI. This video focuses on the skills measured by the exam objectives, as updated by Microsoft in January 2026.

Using his years of experience teaching Power BI to a variety of learners, Chris Sorensen explains how to optimize Power BI features and functions and prepares you for what to expect on the PL-300 exam.  In his engaging style grounded in real-world scenarios, Chris gives you insights to navigate and build Power BI solutions, quickly and effectively. With Chris as your guide, you are well-equipped to advance in your career as a data analyst.

Skill Level:

• Beginner to Intermediate

 Learn How To:

• Prepare for the PL-300 exam
• Prepare the data
• Model the data
• Visualize and analyze the data
• Manage and secure Power BI

Pre-requisites:

• Some experience with Power BI

Who Should Take This Course:

• Certification candidates preparing for exam PL-300 Microsoft Power BI Data Analyst
• Data analysts who want to use Microsoft Power BI to maximize their data assets and deliver actionable insights
• Business intelligence professionals who want to advance their knowledge of data processing and analytics

About the Instructor:

Chris Sorensen CPA, CGA, is the founder and president of Iteration Insights, a Calgary-based Microsoft partner that works in the Data and AI space. Having completed numerous Microsoft Certifications and having more than 20 years of consulting and teaching experience, Chris brings a practical lens to his training, going beyond theory to everyday technology use. Chris has overseen hundreds of data projects across diverse industries, delivering solutions and empowering organizations with analytics. He is a published author for Microsoft Press, covering topics in data analytics, SQL, Power BI, and Microsoft data certification exam prep.

About Pearson Video Training: 

Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que Topics include IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more.  Learn more about Pearson Video training at  http://www.informit.com/video.

Video Lessons are available for download for offline viewing within the streaming format. Look for the green arrow in each lesson.

Sample Content

Table of Contents

Module 1: Prepare the Data
Intro

Lesson 1: Get or Connect to Data
Learning objectives
1.1 Identify and connect to data sources or a shared semantic model
1.2 Change data source settings, including credentials and privacy levels
1.3 Choose between DirectQuery and Import
1.4 Create and modify parameters

Lesson 2: Profile and Clean the Data
Learning objectives
2.1 Evaluate data, including data statistics and column properties
2.2 Resolve inconsistencies, unexpected or null values, and data quality issues
2.3 Resolve data import errors

Lesson 3: Transform and Load the Data
Learning objectives
3.1 Select appropriate column data types
3.2 Create and transform columns
3.3 Group and aggregate rows
3.4 Pivot, unpivot, and transpose data
3.5 Convert semi-structured data to a table
3.6 Create fact tables and dimension tables
3.7 Identify when to use reference or duplicate queries and the resulting impact
3.8 Merge and append queries
3.9 Identify and create appropriate keys for relationships
3.10 Configure data loading for queries

Module 2: Model the Data
Intro

Lesson 4: Design and Implement a Data Model
Learning objectives
4.1 Configure table and column properties
4.2 Implement role-playing dimensions
4.3 Define a relationship's cardinality and cross-filter direction
4.4 Create a common date table
4.5 Identify use cases for calculated columns and calculated tables

Lesson 5: Create Model Calculations by Using DAX
Learning objectives
5.1 Create single aggregation measures
5.2 Use the CALCULATE function
5.3 Implement time intelligence measures
5.4 Use basic statistical functions
5.5 Create semi-additive measures
5.6 Create a measure by using quick measures
5.7 Create calculated tables or columns
5.8 Create calculation groups

Lesson 6: Optimize Model Performance
Learning objectives
6.1 Improve performance by identifying and removing unnecessary rows and columns
6.2 Identify poorly performing measures, relationships, and visuals by using Performance Analyzer and DAX query view
6.3 Improve performance by reducing granularity

Module 3: Visualize and Analyze the Data
Intro

Lesson 7: Create Reports
Learning objectives
7.1 Select an appropriate visual
7.2 Format and configure visuals
7.3 Create a narrative visual with Copilot
7.4 Apply and customize a theme
7.5 Apply conditional formatting
7.6 Apply slicing and filtering
7.7 Use Copilot to create a new report page
7.8 Use Copilot to suggest content for a new report page
7.9 Configure the report page
7.10 Choose when to use a paginated report
7.11 Create visual calculations by using DAX

Lesson 8: Enhance Reports for Usability and Storytelling
Learning objectives
8.1 Configure bookmarks
8.2 Create custom tooltips
8.3 Edit and configure interactions between visuals
8.4 Configure navigation for a report
8.5 Apply sorting to visuals
8.6 Configure sync slicers
8.7 Group and layer visuals by using the Selection pane
8.8 Configure drill-through navigation
8.9 Configure export settings
8.10 Design reports for mobile devices
8.11 Enable personalized visuals in a report
8.12 Design and configure Power BI reports for accessibility
8.13 Configure automatic page refresh

Lesson 9: Identify Patterns and Trends
Learning objectives
9.1 Use the Analyze feature in Power BI
9.2 Use grouping, binning, and clustering
9.3 Use AI visuals
9.4 Use reference lines, error bars, and forecasting
9.5 Detect outliers and anomalies
9.6 Use Copilot to summarize the underlying semantic model

Module 4: Manage and Secure Power BI
Intro

Lesson 10: Create and Manage Workspaces and Assets
Learning objectives
10.1 Create and configure a workspace
10.2 Configure and update a workspace app
10.3 Publish, import, or update items in a workspace
10.4 Create dashboards
10.5 Choose a distribution method
10.6 Configure subscriptions and data alerts
10.7 Promote or certify Power BI content
10.8 Identify when a gateway is required
10.9 Configure a semantic model scheduled refresh

Lesson 11: Secure and Govern Power BI Items
Learning objectives
11.1 Assign workspace roles
11.2 Configure item-level access
11.3 Configure access to semantic models
11.4 Implement row-level security roles
11.5 Configure row-level security group membership
11.6 Apply sensitivity labels

Summary

Updates

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