Course Outline
Module 1: Discover data analysis
In this module, you will explore the different roles within data analytics and learn the specific tasks performed by 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 data analytics.
- Learn the core tasks of a data analyst.
Module 2: Get started building with Power BI
Learn what Power BI is, including its fundamental building blocks and how they integrate to function effectively.
This module helps prepare 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 work together.
- Explore how Power BI can enhance business efficiency.
- Learn to 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
In this module, you will learn how to retrieve data from various sources, including Microsoft Excel, relational databases, and NoSQL data stores. You will also learn techniques to improve 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 a relational database, such as Microsoft SQL Server
- Retrieve data from files, such as Microsoft Excel
- Retrieve data from applications
- Retrieve data from Azure Analysis Services
- Select an appropriate storage mode
- Resolve performance issues
- Fix 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, change data types, rename objects, and pivot data. You will also learn how to profile columns to identify those containing valuable data essential 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 into specific columns before utilization.
- 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 quickly end up with dozens of tables to manage. Building an effective data model involves simplifying this complexity. A star schema is one method to simplify a data model, and this module covers its terminology and implementation. You will also learn why selecting the correct data granularity is crucial for the performance and usability of your Power BI reports. Finally, you will learn how to optimize performance with your Power BI data models.
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
In this module, you will learn how to work with implicit and explicit measures. You will begin by creating simple measures that summarize a single column or table. Then, you will create more complex measures based on other measures within the model. Additionally, you will understand the similarities and differences between a calculated column and a measure.
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 the 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 also learn to describe row context, which is used to evaluate calculated column formulas. Since it is possible to add columns using Power Query, you will also learn when it is best to create 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 instead 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 the concept of time intelligence and how to implement time intelligence DAX calculations in 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, also known as performance tuning, involves modifying the current state of the data model to ensure more efficient execution. Essentially, when your data model is optimized, it performs better.
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 troubleshoot issues.
- 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
Since Power BI includes more than 30 core visuals, selecting the correct visual can be challenging for beginners. This module guides you through selecting the most appropriate visual type to meet your design and report layout requirements.
Learning objectives
In this module, you will:
- Learn about the structure of a Power BI report.
- Understand report objects.
- Select the appropriate visual type for your needs.
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 due to the many available techniques for filtering a Microsoft Power BI report. However, this complexity offers greater control, allowing you to design reports that meet specific requirements and expectations. Some filtering techniques apply at design time, while others are relevant during report consumption (in reading view). The key is ensuring your report design allows consumers to intuitively narrow down to the data points that interest them.
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 to enhance the overall 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 how to use Power BI to perform data analytical functions, identify outliers, group data, and bin data for analysis. You will also learn how to conduct time series analysis. Finally, you will work with advanced analytic features of Power BI, 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 how 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 use a single dataset to build many reports. Further reduce administrative overhead with scheduled dataset refreshes and by 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
Microsoft Power BI dashboards differ from Power BI reports. Dashboards allow report consumers to create a single, personalized artifact of directed data. They can be composed of pinned visuals taken from different reports. While a Power BI report uses data from a single dataset, a Power BI dashboard can contain visuals from different 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) allows you to create a single or a set of reports targeting data for a specific user. In this module, you will learn how to implement RLS using either a static or dynamic method and how Microsoft Power BI simplifies testing RLS in Power BI Desktop and the Power BI service.
Learning objectives
In this module, you will:
- Configure row-level security using a static method.
- Configure row-level security 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 (7)
engagement with the attendees
Magdeline Matsie Mokonyane-Motha - Tshwane University of Technology
Course - PL-300T00: Microsoft Power BI Data Analyst
the practical for mastering how power Bi connect databases
Lemogang Mongake - Tshwane University of Technology
Course - PL-300T00: Microsoft Power BI Data Analyst
I also enjoyed learning about data visualization, dashboard creation, and data modelling, as these skills are highly relevant to modern decision-making and reporting environments. The training was engaging, informative, and directly applicable to professional and academic work.
Jean Claude Fwamba - Tshwane University of Technology
Course - PL-300T00: Microsoft Power BI Data Analyst
Well presented
Winston Zitha - Tshwane University of Technology
Course - PL-300T00: Microsoft Power BI Data Analyst
He is good with people
James Magidi - Tshwane University of Technology
Course - PL-300T00: Microsoft Power BI Data Analyst
great lecture
kabelo madumo - Tshwane University of Technology
Course - PL-300T00: Microsoft Power BI Data Analyst
He made me understand the course and enjoy
