6+ Hours of Video Instruction
Prepare for Microsoft Exam PL-300 and demonstrate your mastery of Power BI data analysis.
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, …
6+ Hours of Video Instruction
Prepare for Microsoft Exam PL-300 and demonstrate your mastery of Power BI data analysis.
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 on February 28, 2022:
Using his years of experience teaching Power BI to a variety of learners, Microsoft Certified Trainer 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 that is grounded in real-world scenarios, Chris gives you insights to navigate and build effective Power BI solutions, quickly and effectively. With Chris as your guide, you are well-equipped to advance in your career as a data analyst.
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Introduction
Exam PL-300 Microsoft Power BI Data Analyst: Introduction
Module 1: Prepare the Data
Module Introduction
Lesson 1: Get Data from Different Data Sources
Learning objectives
1.1 Identify and connect to a data source
1.2 Change data source settings
1.3 Select a shared dataset or create a local dataset
1.4 Select a storage mode
1.5 Use Microsoft Dataverse
1.6 Change the value in a parameter
1.7 Connect to a data flow
Lesson 2: Clean, Transform, and Load the Data
Learning objectives
2.1 Profile the data
2.2 Resolve inconsistencies, unexpected or null values, and data quality issues
2.3 Identify and create appropriate keys for joins
2.4 Evaluate and transform column data types
2.5 Shape and transform tables
2.6 Combine queries
2.7 Apply user-friendly naming conventions to columns and queries
2.8 Configure data loading
2.9 Resolve data import errors
Module 2: Model the Data
Module Introduction
Lesson 3: Design a Data Model
Learning objectives
3.1 Define the tables and design a data model that uses a star schema
3.2 Configure table and column properties
3.3 Design and implement role-playing dimensions
3.4 Define a relationship’s cardinality and cross-filter direction
3.5 Create a common date table
Lesson 4: Develop a Data Model
Learning objectives
4.1 Create calculated tables
4.2 Create hierarchies
4.3 Create calculated columns
4.4 Implement row-level security roles
4.5 Use the Q feature
Lesson 5: Create Model Calculations by Using DAX
Learning objectives
5.1 Create basic measures by using DAX
5.2 Use CALCULATE to manipulate filters
5.3 Implement Time Intelligence using DAX
5.4 Replace implicit measures with explicit measures
5.5 Use basic statistical functions
5.6 Create semi-additive measures
5.7 Use quick measures
Lesson 6: Optimize Model Performance
Learning objectives
6.1 Remove unnecessary rows and columns
6.2 Identify poorly performing measures, relationships, and visuals
6.3 Reduce cardinality levels to improve performance
Module 3: Visualize and Analyze the Data
Module Introduction
Lesson 7: Create Reports
Learning objectives
7.1 Add visualization items to reports
7.2 Choose an appropriate visualization type
7.3 Format and configure visualizations
7.4 Use a custom visual
7.5 Apply and customize a theme
7.6 Configure conditional formatting
7.7 Apply slicing and filtering
7.8 Configure the report page
7.9 Use the Analyze in Excel feature
7.10 Choose when to use a paginated report
Lesson 8: Create Dashboards
Learning objectives
8.1 Manage tiles on a dashboard
8.2 Configure mobile view
8.3 Use the Q feature
8.4 Add a Quick Insights result to a dashboard
8.5 Apply a dashboard theme
8.6 Pin a live report page to a dashboard
Lesson 9: Enhance Reports for Usability and Storytelling
Learning objectives
9.1 Configure bookmarks
9.2 Create custom tooltips
9.3 Edit and configure interactions between visuals
9.4 Configure navigation for a report
9.5 Apply sorting
9.6 Configure Sync Slicers
9.7 Group and layer visuals by using the selection pane
9.8 Drilldown into data using interactive visuals
9.9 Export report data
9.10 Design reports for mobile devices
Lesson 10: Identify Patterns and Trends
Learning objectives
10.1 Use the Analyze feature in Power BI
10.2 Identify outliers
10.3 Choose between continuous and categorical axes
10.4 Use groupings, binnings, and clustering
10.5 Use AI visuals
10.6 Use the Forecast feature
10.7 Create reference lines by using the Analytics pane
Module 4: Deploy and Maintain Assets
Module Introduction
Lesson 11: Manage Files and Datasets
Learning objectives
11.1 Identify when a gateway is required
11.2 Configure a dataset scheduled refresh
11.3 Configure row-level security group membership
11.4 Provide access to datasets
11.5 Manage global options for files
Lesson 12: Manage Workspaces
Learning objectives
12.1 Create and configure a workspace
12.2 Assign workspace roles
12.3 Configure and update a workspace app
12.4 Publish, import, or update assets in a workspace
12.5 Apply sensitivity labels to workspace content
12.6 Configure subscriptions and data alerts
12.7 Promote or certify Power BI content
Summary
Exam PL-300 Microsoft Power BI Data Analyst: Summary