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Over 5 Hours of Video Instruction
Fully Updated! Prepare for Microsoft Exam PL-300 and level up in your career as a Power BI data analyst.
Overview:
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 April 2024:
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
Course Requirements
Who Should Take This Course
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Video Lessons are available for download for offline viewing within the streaming format. Look for the green arrow in each lesson.
Introduction
Module 1: Prepare the Data
Lesson 1: Get data from data sources
Learning objectives
1.1 Identify and connect to a data source
1.2 Change data source settings, including credentials, privacy levels, and data source locations
1.3 Select a shared semantic model, or create a local semantic model
1.4 Choose between DirectQuery, Import, and Dual mode
1.5 Change the value in a parameter
Lesson 2: 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 Transform a query
3.4 Design a star schema that contains facts and dimensions
3.5 Identify when to use reference or duplicate queries and the resulting impact
3.6 Merge and append queries
3.7 Identify and create appropriate keys for relationships
3.8 Configure data loading for queries
Module 2: Model the Data
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 Implement row-level security roles
Lesson 5: Create model calculations by using DAX
Learning objectives
5.1 Create single aggregation measures
5.2 Use CALCULATE to manipulate filters
5.3 Implement time intelligence measures
5.4 Identify implicit measures and replace with explicit measures
5.5 Use basic statistical functions
5.6 Create semi-additive measures
5.7 Create a measure by using quick measures
5.8 Create calculated tables
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
6.3 Improve performance by choosing optimal data types
6.4 Improve performance by summarizing data
Module 3: Visualize and Analyze the Data
Lesson 7: Create reports
Learning objectives
7.1 Identify and implement appropriate visualizations
7.2 Format and configure visualizations
7.3 Use a custom visual
7.4 Apply and customize a theme
7.5 Configure conditional formatting
7.6 Apply slicing and filtering
7.7 Configure the report page
7.8 Use the Analyze in Excel feature
7.9 Choose when to use a paginated report
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
8.6 Configure sync slicers
8.7 Group and layer visuals by using the Selection pane
8.8 Drill down into data using interactive visuals
8.9 Configure export of report content, and perform an export
8.10 Design reports for mobile devices
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 Incorporate the Q&A feature in a report
9.4 Use AI visuals
9.5 Use reference lines, error bars, and forecasting
9.6 Detect outliers and anomalies
9.7 Create and share scorecards and metrics
Module 4: Deploy and Maintain Assets
Lesson 10: Create and manage workspaces and items
Learning objectives
10.1 Create and configure a workspace
10.2 Assign workspace roles
10.3 Configure and update a workspace app
10.4 Publish, import, or update items in a workspace
10.5 Create dashboards
10.6 Choose a distribution method
10.7 Apply sensitivity labels to workspace content
10.8 Configure subscriptions and data alerts
10.9 Promote or certify Power BI content
10.10 Manage global options for files
Lesson 11: Manage semantic models
Learning objectives
11.1 Identify when a gateway is required
11.2 Configure a semantic model scheduled refresh
11.3 Configure row-level security group membership
11.4 Provide access to semantic models
Summary