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MS-PL300T00: Design and Manage Analytics Solutions Using Power BI
Course Code: MS-PL300T00
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.
The audience for this course is 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.
Successful Data Analysts start this role with experience of working with data in the cloud.
Specifically:
- Understanding core data concepts.
- Knowledge of working with relational data in the cloud.
- Knowledge of working with non-relational data in the cloud.
- Knowledge of data analysis and visualization concepts.
You can gain the prerequisites and a better understanding of working with data in Azure by completing Microsoft Azure Data Fundamentals before taking this course.
After completing this course, students will be able to:
- Ingest, clean, and transform data
- Model data for performance and scalability
- Design and create reports for data analysis
- Apply and perform advanced report analytics
- Manage and share report assets
- Create paginated reports in Power BI
This course will prepare delegates to write the Microsoft PL-300: Microsoft Power BI Data Analyst exam.
Modules
Would you like to explore the journey of a data analyst and learn how a data analyst tells a story with data? In this module, you explore the different roles in data and learn the different tasks of a data analyst.
Lessons
- Introduction
- Overview of data analysis
- Roles in data
- Tasks of a data analyst
- Check your knowledge
- Summary
After completing this module, students will:
- Learn about the roles in data
- Learn about the tasks of a data analyst
Learn about Power BI, the building blocks and flow of Power BI, and how to create compelling, interactive reports.
Lessons
- Introduction
- Use Power BI
- Building blocks of Power BI
- Tour and use the Power BI service
- Check your knowledge
- Summary
After completing this module, students will:
- 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
Discover how Microsoft Fabric can meet your enterprise's analytics needs in one platform. Learn about Microsoft Fabric, how it works, and identify how you can use it for your analytics needs.
Lessons
- Introduction
- Explore end-to-end analytics with Microsoft Fabric
- Explore data teams and Microsoft Fabric
- Enable and use Microsoft Fabric
- Module assessment
- Summary
After completing this module, students will:
- Identify the capabilities of Microsoft Fabric.
- Implement Microsoft Fabric to meet your enterprise's analytics needs.
Copilot in Power BI increases productivity when developing semantic models and reports using Power BI. Copilot also allows you to interact with your data using natural language to gain insights.
Lessons
- Introduction
- Use Copilot in Power BI to prepare and model data
- Create reports with Copilot in Power BI
- Get your data ready for Al usage in Power BI
- Module assessment
- Summary
By the end of this module, you'll understand how to:
- Use Copilot in Power BI during report development.
- Prepare semantic models for use with AI.
- Interact with data using natural language in Copilot Chat.
You'll learn how to retrieve data from a variety of data sources, including Microsoft Excel, relational databases, and NoSQL data stores. You'll also learn how to improve performance while retrieving data.
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
After completing this module, students will:
- 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
Power Query has an incredible number of features that are dedicated to helping you clean and prepare your data for analysis. You'll learn how to simplify a complicated model, change data types, rename objects, and pivot data. You'll also learn how to profile columns so that you know which columns have the valuable data that you’re seeking for deeper analytics.
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
After completing this module, students will be able to:
- 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.
Describe model frameworks, their benefits and limitations, and features to help optimize your Power BI data models.
Lessons
- Introduction
- Describe Power BI model fundamentals
- Determine when to develop an import model
- Determine when to develop a DirectQuery model
- Determine when to develop a composite model
- Choose a model framework
- Check your knowledge
- Summary
After completing this module, students will be able to:
- Describe Power BI model fundamentals
- Determine when to develop an import model
- Determine when to develop a DirectQuery model
- Determine when to develop a composite model
- Choose an appropriate Power BI model framework
Semantic models organize complex data into an intuitive structure, enhancing data visualization and enabling efficient, insightful reporting for better decision-making.
Lessons
- Introduction
- Configure relationships
- Configure tables
- Configure columns
- Configure hierarchies
- Configure measures
- Configure parameters
- Exercise - Configure a semantic model in Power BI Desktop
- Check your knowledge
- Summary
In this module, you learn how to:
- Set modeling options.
- Create and configure relationships.
- Configure table and column properties.
- Create hierarchies.
- Create quick measures.
- Create numeric range and field parameters.
Data Analysis Expressions (DAX) is a formula language for Power BI that enables you to create calculations, add logic, and enhance data analysis within your reports and semantic models.
Lessons
- Introduction
- Understand DAX calculation types
- Write DAX formulas
- DAX data types
- Work with DAX functions
- Use DAX operators
- Use DAX variables
- Check your knowledge
- Summary
In this module, you learn how to:
- Describe the different DAX calculation types.
- Write DAX formulas.
- Describe DAX data types.
- Work with DAX functions.
- Use DAX operators.
- Use DAX variables.
Adding DAX calculations to Power BI semantic models allows you to define custom logic within your data model, to enable deeper analysis and data-driven business decisions.
Lessons
- Introduction
- Create calculated tables
- Create calculated columns
- Understand implicit measures
- Create explicit measures
- Use iterator functions
- Exercise - Create DAX calculations
- Check your knowledge
- Summary
In this module, you learn how to:
- Create calculated tables.
- Create calculated columns.
- Create measures using DAX.
DAX time intelligence functions in Power BI enable users to analyze and compare data across different time periods, supporting insightful reporting on trends, growth, and performance over time.
Lessons
- Introduction
- Use DAX time intelligence functions
- Additional time intelligence calculations
- Exercise - Use time intelligence functions
- Check your knowledge
- Summary
By the end of this module, you'll be able to:
- Define time intelligence.
- Use common DAX time intelligence functions.
- Create useful intelligence calculations.
Calculations in Power BI are necessary to enrich data analysis. Visual calculations simplify complex formulas, enhance performance, and reduce maintenance.
Lessons
- Introduction
- Understand visual calculations
- Create visual calculations
- Use parameters in visual calculations
- Exercise - Create visual calculations in Power BI Desktop
- Knowledge check
- Summary
After completing this module, students will be able to:
- Understand visual calculations and how they differ from measures.
- Create visual calculations in Power BI Desktop.
- Use parameters in visual calculations.
Performance optimization, also known as performance tuning, involves making changes to the current state of the semantic model so that it runs more efficiently. Essentially, when your semantic model is optimized, it performs better.
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
After completing this module, students 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
Identify your audience, choose suitable report types, and define interface and experience requirements to effectively plan your report design.
Lessons
- Introduction
- Identify the audience
- Determine report types
- Define user interface requirements
- Define user experience requirements
- Explore report designs
- Check your knowledge
- Summary
After completing this module, students will be able to:
- Determine business goals
- Identify your audience
- Determine report types
- Define user interface requirements
- Define user experience requirements
Design effective Power BI reports that are visually appealing and easy to understand with consistent report structure, interactive objects, and filtering.
Lessons
- Introduction
- Design the analytical report layout
- Design visually appealing reports
- Use report objects
- Select report visuals
- Apply filters and slicers to reports
- Understand filtering techniques and considerations
- Case study - Configure report filters based on feedback
- Exercise - Design Power BI reports
- Check your knowledge
- Summary
After completing this module, students will be able to:
- Report structure.
- Report objects.
- Different visualization types.
Design reports with intuitive navigation and enable users to explore data in an easy way that is meaningful to them.
Lessons
- Introduction
- 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
In this module, you learn how to:
- Design reports that present details and highlight key values.
- Build interactive reports with intuitive navigation and app-like experiences.
- Enhance user experience using bookmarks, visual headers, and built-in assistance.
- Incorporate specialized visuals to meet unique reporting needs.
Advanced analytics helps you gain deeper insights into your data, identify trends, and make data-driven decisions. Power BI provides a variety of tools and features to help you analyze your data effectively.
Lessons
- Introduction
- Explore a 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 Al Visuals
- Check your knowledge
- Summary
After completing this module, students will be able to:
- Create a 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
Explore the Power BI service, create and manage workspaces, and distribute reports to users.
Lessons
- Introduction
- Understand Power BI service
- Understand workspaces
- Publish to Power BI service
- Check your knowledge
- Summary
In this module, you will:
- Describe the Power BI service and its building blocks.
- Create workspaces, assign license modes, and manage access.
- Publish reports to the Power BI service.
Semantic models are the foundation for report development in Power BI. Efficient management ensures data connectivity and improves report performance and accuracy.
Lessons
- 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
- Boost performance with query caching (Fabric or Premium capacity)
- Use lineage and impact analysis
- Check your knowledge
- Summary
In this module, you will:
- Manage data source connectivity and gateways.
- Configure semantic model refresh settings.
- Endorse semantic models.
- Analyze data dependencies.
- Configure query caching with Fabric or Premium capacities.
Choose a content distribution method for Power BI.
Lessons
- Introduction
- Understand sharing models
- Create a Power BI app
- Apply data governance principles
- Track report or dashboard usage
- Check your knowledge
- Summary
In this module, you will:
- Understand the different content distribution methods available in Power BI
- Create a Power BI app
- Apply data governance principles
- Track a report or dashboard
Microsoft Power BI dashboards are different than Power BI reports. Dashboards allow report consumers to create a single artifact of directed data that is personalized just for them. Dashboards can be composed of pinned visuals that are taken from different reports. Where a Power BI report uses data from a single semantic model, a Power BI dashboard can contain visuals from different semantic models.
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
- Set mobile view
- Exercise - Create a Power BI dashboard
- Check your knowledge
- Summary
After completing this module, students will be able to:
- Create a dashboard.
- Configure data alerts.
- Ask questions using Q&A.
- Review Quick insights
- Add a theme to the visuals in your dashboard.
- Pin a live report page to a dashboard.
- Set a mobile view.
Row-level security (RLS) and Object-level security (OLS) allows you to create a single or a set of reports that targets data for a specific user. In this module, you’ll learn how to implement RLS by using either a static or dynamic method and how Microsoft Power BI simplifies testing RLS in Power BI Desktop and Power BI service. In addition, you’ll learn how to implement OLS to restrict access to Power BI model objects.
Lessons
- Introduction
- Configure row-level security with the static method
- Configure row-level security with the dynamic method
- Use single sign-on (SSO) for DirectQuery sources
- Restrict access to Power BI model objects
- Exercise - Enforce row-level security in Power BI
- Check your knowledge
- Summary
In this module, you will:
- Configure row-level security by using a static method.
- Configure row-level security by using a dynamic method.
- Use single sign-on (SSO) for DirectQuery sources
- Restrict access to Power BI model objects with object-level security.