Course Outline
Module 1: Discover data analysis
In this module, you will explore different data roles and understand the specific responsibilities of a data analyst.
Lessons
- Introduction
- Overview of data analysis
- Roles in data
- Tasks of a data analyst
- Check your knowledge
- Summary
Learning objectives
Upon completing this module, students will be able to:
- Understand the various roles within the data field.
- Identify the key tasks performed by a data analyst.
Module 2: Get started building with Power BI
Gain an understanding of Power BI, including its core components and how they integrate.
This module prepares you for Exam PL-100: Microsoft Power Platform App Maker.
Learning objectives
Upon completing this module, students will be able to:
- Understand how Power BI services and applications interact.
- Explore how Power BI enhances business efficiency.
- Create compelling visuals and reports.
Lessons
- 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
Learn to retrieve data from various sources, such as Microsoft Excel, relational databases, and NoSQL stores. You will also discover methods to enhance performance during data retrieval.
Learning objectives
By the end of this module, you will be able to:
- Identify and connect to a data source.
- Retrieve data from relational databases, such as Microsoft SQL Server.
- Retrieve data from files, such as Microsoft Excel.
- Retrieve data from applications.
- Retrieve data from Azure Analysis Services.
- Select a storage mode.
- Troubleshoot performance issues.
- Resolve data import errors.
Lessons
- 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
This module teaches you how to simplify complex models, modify data types, rename objects, and pivot data. You will also learn to profile columns to identify valuable data for deeper analytics.
Learning objectives
By the end of this module, you will be able to:
- Resolve inconsistencies, unexpected or null values, and data quality issues.
- Apply user-friendly value replacements.
- Profile data to gain insights about specific columns before use.
- 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.
Lessons
- 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 data model in Power BI
Creating a complex data model in Power BI is straightforward. When data originates from multiple transactional systems, you may encounter numerous tables. Building an effective data model involves simplifying this complexity. This module covers star schemas as a method for simplification, including terminology and implementation. You will also understand the importance of correct data granularity for performance and usability, and learn techniques for improving data model performance.
Learning objectives
In this module, you will:
- Create common date tables.
- Configure many-to-many relationships.
- Resolve circular relationships.
- Design star schemas.
Lessons
- 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
This module covers working with implicit and explicit measures. You will start by creating simple measures that summarize single columns or tables, then progress to complex measures based on existing model measures. Additionally, you will explore the similarities and differences between calculated columns and measures.
Learning objectives
By the end of this module, you will be able to:
- Determine when to use implicit and explicit measures.
- Create simple measures.
- Create compound measures.
- Create quick measures.
- Describe similarities and differences between a calculated column and a measure.
Lessons
- 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
By the end of this module, you will be able to add calculated tables and columns to your data model. You will understand row context, which is used to evaluate calculated column formulas. Since columns can be added via Power Query, you will also learn when to use calculated columns instead of Power Query custom columns.
Learning objectives
By the end of this module, you will be able to:
- 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 using DAX calculations.
Lessons
- 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
By the end of this module, you will understand time intelligence and how to add time intelligence DAX calculations to your model.
Learning objectives
By the end of this module, you will be able to:
- Define time intelligence.
- Use common DAX time intelligence functions.
- Create useful intelligence calculations.
Lessons
- 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
Performance optimization, or performance tuning, involves modifying the data model to improve efficiency. An optimized data model delivers better performance.
Learning objectives
By the end of this module, you will be able to:
- 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.
Lessons
- Introduction to performance optimization
- Review performance of measures, relationships, and visuals
- 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
With over 30 core visuals in Power BI, selecting the right one can be challenging for beginners. This module guides you in choosing the most appropriate visual type to meet your design and layout requirements.
Learning objectives
In this module, you will:
- Learn about the structure of a Power BI report.
- Learn about report objects.
- Select the appropriate visual type to use.
Lessons
- 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
Report filtering is a complex topic with many techniques available. However, this complexity provides control, enabling you to design reports that meet specific requirements. Some techniques apply at design time, while others apply during report consumption (reading view). The goal is to ensure your report design allows consumers to intuitively narrow down to relevant data points.
Learning objectives
In this module, you will:
- Design reports for filtering.
- Design reports with slicers.
- Design reports using advanced filtering techniques.
- Apply consumption-time filtering.
- Select appropriate report filtering techniques.
Lessons
- 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
Module 12: Enhance Power BI report designs for the user experience
The features and capabilities covered in this module will help you refine your reports for a superior user experience.
Learning objectives
In this module, you will:
- 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.
Lessons
- 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
You will learn to use Power BI for data analytical functions, identify data outliers, group data, and bin data for analysis. Additionally, you will perform time series analysis and work with advanced features such as Quick Insights, AI Insights, and the Analyze feature.
Learning objectives
In this module, you will:
- 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.
Lessons
- 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
Learn to navigate the Power BI service, create and manage workspaces and related items, and distribute reports to users.
Learning objectives
In this module, you will:
- 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.
Lessons
- 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 datasets in Power BI
With Microsoft Power BI, you can build multiple reports from a single dataset. You can further reduce administrative overhead by scheduling dataset refreshes and resolving connectivity errors.
Learning objectives
In this module, you will:
- Use a Power BI gateway to connect to on-premises data sources.
- Configure a scheduled refresh for a dataset.
- Configure incremental refresh settings.
- Manage and promote datasets.
- Troubleshoot service connectivity.
- Boost performance with query caching (Premium).
Lessons
- Introduction
- Use a Power BI gateway to connect to on-premises data sources
- Configure a dataset scheduled refresh
- Configure incremental refresh settings
- Manage and promote datasets
- Troubleshoot service connectivity
- Boost performance with query caching (Premium)
- Check your knowledge
- Summary
Module 16: Create dashboards in Power BI
Power BI dashboards differ from Power BI reports. Dashboards allow consumers to create a personalized, single-artifact view of directed data. They are composed of pinned visuals from various reports. While a Power BI report uses data from a single dataset, a dashboard can contain visuals from multiple datasets.
Learning objectives
In this module, you will:
- 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.
Lessons
- 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
- Configure data classification
- Set mobile view
- Exercise - Create a Power BI dashboard
- Check your knowledge
- Summary
Module 17: Implement row-level security
Row-level security (RLS) enables you to create reports that target data for specific users. This module teaches you to implement RLS using static or dynamic methods and explains how Microsoft Power BI simplifies testing RLS in both Power BI Desktop and the Power BI service.
Learning objectives
In this module, you will:
- Configure row-level security by using a static method.
- Configure row-level security by using a dynamic method.
Lessons
- 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
Requirements
Testimonials (1)
The subject was taught in an engaging way, making me want to learn more.
