Course Outline
Module 1: Discover data analysis
This module introduces the various roles within the data field and outlines the core 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 completion of this module, learners will be able to:
- Understand the distinct roles in data.
- Understand the tasks of a data analyst.
Module 2: Get started building with Power BI
This section explains the components of Power BI and how they interact. It also prepares participants for Exam PL-100: Microsoft Power Platform App Maker.
Learning objectives
Upon completion of this module, learners will be able to:
- Understand how Power BI services and applications integrate.
- Evaluate 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
Participants will learn to retrieve data from diverse sources, including Microsoft Excel, relational databases, and NoSQL stores, while implementing strategies to improve retrieval performance. This content is designed for government professionals seeking efficient data integration solutions.
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 a storage mode
- Address 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 instructs users on simplifying complex models, modifying data types, renaming objects, and pivoting data. It also covers column profiling to identify high-value 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 assess specific columns prior to use.
- Evaluate and transform column data types.
- Apply data shape transformations to table structures.
- Combine queries.
- Apply consistent 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 complex data models in Power BI is streamlined through proper design. When integrating data from multiple transactional systems, users often manage dozens of tables. This module focuses on simplifying disarray using star schemas and emphasizes the importance of data granularity for report performance and usability.
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 implicit and explicit measures. Participants will create simple measures summarizing single columns or tables, then progress to complex measures derived from existing model data. It also distinguishes 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 of, 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
Learners will add calculated tables and columns to their data models and understand row context for evaluating formulas. The module clarifies when to utilize calculated columns over 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 by 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
This module defines time intelligence and demonstrates how to implement time-based DAX calculations within the data 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 tuning, involves modifying the data model to enhance efficiency. An optimized model delivers superior operational 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 available, selecting the appropriate option can be challenging for beginners. This module guides users in choosing visuals that align with design and layout requirements.
Learning objectives
In this module, you will:
- Understand the structure of a Power BI report.
- Understand 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
Filtering in Power BI involves multiple techniques that provide control over report design. Some filters apply at design time, while others function during consumption (reading view). Effective design ensures users can intuitively narrow data points.
Learning objectives
In this module, you will:
- Design reports for filtering.
- Design reports with slicers.
- Design reports by 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
This module covers features that refine report functionality and improve 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
Learners will use Power BI for data analytical functions, including identifying outliers, grouping data, and binning. The module also covers time series analysis and advanced features such as Quick Insights, AI Insights, and the Analyze feature.
Learning objectives
In this module, you'll:
- 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
This section covers navigating the Power BI service, creating and managing workspaces, and distributing reports. It provides guidance for government entities on governance and data sharing protocols.
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
Power BI allows multiple reports to share a single dataset. This module covers scheduled refreshes, connectivity error resolution, and gateway configuration for on-premises data access.
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
Dashboards consolidate visuals from various reports into a single artifact for personalized user consumption. Unlike reports tied to a single dataset, dashboards can aggregate 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) restricts data access to specific users within a report. This module details static and dynamic RLS implementation and testing procedures in Power BI Desktop and the 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 (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
