Course Overview:

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.

Course Objectives:

• Learn about the roles in data.
• Learn about the tasks of a data analyst.
• How Power BI services and applications work together.
• Explore how Power BI can make your business more efficient.
• How to create compelling visuals and reports.
• 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
• 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.
• Create common date tables
• Configure many-to-many relationships
• Resolve circular relationships
• Design star schemas
• 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.
• 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.
• Define time intelligence.
• Use common DAX time intelligence functions.
• Create useful intelligence calculations.
• 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.
• Learn about the structure of a Power BI report.
• Learn about report objects.
• Select the appropriate visual type to use.
• Design reports for filtering.
• Design reports with slicers.
• Design reports by using advanced filtering techniques.
• Apply consumption-time filtering.
• Select appropriate report filtering techniques.
• 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.
• 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.
• 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.
• 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).
• Set a mobile view.
• Add a theme to the visuals in your dashboard.
• Add real-time semantic model visuals to your dashboards.
• Pin a live report page to a dashboard.
• Configure row-level security by using a static method.
• Configure row-level security by using a dynamic method.

Who Should Attend?

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 Prerequisites

There are no prerequisites for this course.

Course Content:

Module 1 : Discover data analysis
Introduction
Overview of data analysis
Roles in data
Tasks of a data analyst
Check your knowledge
Summary

Module 2: Get started building with Power BI
Introduction
Use Power BI
Building blocks of Power BI
Tour and use the Power BI service
Knowledge check
Summary

Module 3: Get data in Power BI
Introduction
Get data from files
Get data from relational data sources
Create dynamic reports with parameters
Get data from a NoSQL database
Get data from online services
Select a storage mode
Get data from Azure Analysis Services
Fix performance issues
Resolve data import errors
Exercise – Prepare data in Power BI Desktop
Check your knowledge
Summary

Module 4: Clean, transform, and load data in Power BI
Introduction
Shape the initial data
Simplify the data structure
Evaluate and change column data types
Combine multiple tables into a single table
Profile data in Power BI
Use Advanced Editor to modify M code
Exercise – Load data in Power BI Desktop
Check your knowledge
Summary

Module 5: Design a semantic model in Power BI
Introduction
Work with tables
Create a date table
Work with dimensions
Define data granularity
Work with relationships and cardinality
Resolve modeling challenges
Exercise – Model data in Power BI Desktop
Check your knowledge
Summary

Module 6: Add measures to Power BI Desktop models
Introduction
Create simple measures
Create compound measures
Create quick measures
Compare calculated columns with measures
Check your knowledge
Exercise – Create DAX Calculations in Power BI Desktop
Summary

Module 7: Add calculated tables and columns to Power BI Desktop models
Introduction
Create calculated columns
Learn about row context
Choose a technique to add a column
Check your knowledge
Summary

Module 8: Use DAX time intelligence functions in Power BI Desktop models
Introduction
Use DAX time intelligence functions
Additional time intelligence calculations
Exercise – Create Advanced DAX Calculations in Power BI Desktop
Check your knowledge
Summary

Module 9: Optimize a model for performance in Power BI
Introduction to performance optimization
Review performance of measures, relationships, and visuals
19 min
Use variables to improve performance and troubleshooting
Reduce cardinality
Optimize DirectQuery models with table level storage
Create and manage aggregations
Check your knowledge
Summary

Module 10: Design Power BI reports
Introduction
Design the analytical report layout
Design visually appealing reports
Report objects
Select report visuals
Select report visuals to suit the report layout
Format and configure visualizations
Work with key performance indicators
Exercise – Design a report in Power BI desktop
Check your knowledge
Summary

Module 11: Configure Power BI report filters
Introduction to designing reports for filtering
Apply filters to the report structure
Apply filters with slicers
Design reports with advanced filtering techniques
Consumption-time filtering
Select report filter techniques
Case study – Configure report filters based on feedback
Check your knowledge
Summary

Modul 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
Tune report performance
Optimize reports for mobile use
Exercise – Enhance Power BI reports
Check your knowledge
Summary

Module 13: Perform analytics in Power BI
Introduction to analytics
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
Create what-if parameters
Use specialized visuals
Exercise – Perform Advanced Analytics with AI Visuals
Check your knowledge
Summary

Module 14: Create and manage workspaces in Power BI
Introduction
Distribute a report or dashboard
Monitor usage and performance
Recommend a development life cycle strategy
Troubleshoot data by viewing its lineage
Configure data protection
Check your knowledge
Summary

Module 15: Manage semantic models in Power BI
Introduction
Use a Power BI gateway to connect to on-premises data sources
Configure a semantic model scheduled refresh
Configure incremental refresh settings
Manage and promote semantic models
Troubleshoot service connectivity
Boost performance with query caching (Premium)
Check your knowledge
Summary

Module 16: Create dashboards in Power BI
Introduction to dashboards
Configure data alerts
Explore data by asking questions
Review Quick insights
Add a dashboard theme
Pin a live report page to a dashboard
Configure a real-time dashboard
Set mobile view
Exercise – Create a Power BI dashboard
Check your knowledge
Summary

Module 17: Implement row-level security
Introduction
Configure row-level security with the static method
Configure row-level security with the dynamic method
Exercise – Enforce row-level security in Power BI
Check your knowledge
Summary