Microsoft Power BI Data Analyst

Course number: CGIPBIDA40

This course covers the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will show how to access and process data from a range of data sources including both relational and non-relational sources. Finally, this course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution.

Students will learn to:

Discover data analysis
Get started building with Power BI
Get data in Power BI
Clean, transform, and load data in Power BI
Design a semantic model in Power BI
Add measures to Power BI Desktop models
Add calculated tables and columns to Power BI Desktop models
Use DAX time intelligence functions in Power BI Desktop models
Optimize a model for performance in Power BI
Design Power BI reports
Configure Power BI report filters
Enhance Power BI report designs for the user experience
Perform analytics in Power BI
Create and manage workspaces in Power BI
Manage semantic models in Power BI
Create dashboards in Power BI
Implement row-level security

Target Audience

The audience for this course are data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist on both in the cloud and on-premises.

Course Content

Module 1: Discover data analysis

Learn about the roles in data.
Learn about the tasks of a data analyst

Module 2: Get started building with Power BI

Learn how Power BI services and applications work together
Explore how Power BI can make your business more efficient
Learn how to create compelling visuals and reports

Module 3: Get data in Power BI

Identify and connect to a data source
Get data from a relational database, like Microsoft SQL Server
Get data from a file, like Microsoft Excel
Get data from applications
Get data from Azure Analysis Services
Select a storage mode
Fix performance issues
Resolve data import errors

Module 4: Clean, transform and load data in Power BI

Resolve inconsistencies, unexpected or null values, and data quality issues
Apply user-friendly value replacements
Profile data so you can learn more about a specific column before using it
Evaluate and transform column data types
Apply data shape transformations to table structures
Combine queries
Apply user-friendly naming conventions to columns and queries
Edit M code in the Advanced Editor

Module 5: Design a semantic model in Power BI

Create common date tables
Configure many-to-many relationships
Resolve circular relationships
Design star schemas

Module 6: Add measures to Power BI Desktop models

Determine when to use implicit and explicit measures
Create simple measures
Create compound measures
Create quick measures
Describe similarities of, and differences between, a calculated column and a measure

Module 7: Add calculated tables and columns to Power BI Desktop models

Create calculated tables
Create calculated columns
Identify row context
Determine when to use a calculated column in place of a Power Query custom column
Add a date table to your model by using DAX calculations

Module 8: Use DAX time intelligence functions in Power BI Desktop models

Define time intelligence
Use common DAX time intelligence functions
Create useful intelligence calculations

Module 9: Optimize a model for performance in Power BI

Review the performance of measures, relationships, and visuals
Use variables to improve performance and troubleshooting
Improve performance by reducing cardinality levels
Optimize DirectQuery models with table level storage
Create and manage aggregations

Module 10: Design Power BI reports

Learn about the structure of a Power BI report
Learn about report objects
Select the appropriate visual type to use

Module 11: Configure Power BI report filters

Design reports for filtering
Design reports with slicers
Design reports by using advanced filtering techniques
Apply consumption-time filtering
Select appropriate report filtering techniques

Module 12 : Enhance Power BI report designs for the user experience

Design reports to show details
Design reports to highlight values
Design reports that behave like apps
Work with bookmarks
Design reports for navigation
Work with visual headers
Design reports with built-in assistance
Use specialized visuals

Module 13: Perform analytics in Power BI

Explore statistical summary
Identify outliers with Power BI visuals
Group and bin data for analysis
Apply clustering techniques
Conduct time series analysis
Use the Analyze feature
Use advanced analytics custom visuals
Review Quick insights
Apply AI Insights

Module 14: Create and manage workspaces in Power BI

Create and manage Power BI workspaces and items
Distribute a report or dashboard
Monitor usage and performance
Recommend a development lifecycle strategy
Troubleshoot data by viewing its lineage
Configure data protection

Module 15: Manage semantic models in Power BI

Use a Power BI gateway to connect to on-premises data sources
Configure a scheduled refresh for a semantic model
Configure incremental refresh settings
Manage and promote semantic models
Troubleshoot service connectivity
Boost performance with query caching (Premium)

Module 16: Create dashboards in Power BI

Set a mobile view
Add a theme to the visuals in your dashboard
Configure data classification
Add real-time dataset visuals to your dashboards
Pin a live report page to a dashboard

Module 17: Implement row-level security

Configure row-level security by using a static method
Configure row-level security by using a dynamic method

Available Formats

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