Learning Path 1: Get started with Microsoft data analytics
Explore the role of a data analyst and how Power BI tools transform data into impactful reports and dashboards that support trusted, data-driven decisions across the business.

Module 1: Discover data analysis
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
•   Overview of data analysis
•   Roles in data
•   Tasks of a data analyst

Module 2: Get started building with Power BI
Learn about Power BI, the building blocks and flow of Power BI, and how to create compelling, interactive reports.
Lessons
•   Use Power BI
•   Building blocks of Power BI
•   Tour and use the Power BI service

Module 3: Introduction to end-to-end analytics using Microsoft Fabric
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
•   Explore end-to-end analytics with Microsoft Fabric
•   Explore data teams and Microsoft Fabric
•   Enable and use Microsoft Fabric

Module 4: Get started with Copilot in Power BI
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
•   Use Copilot in Power BI to prepare and model data
•   reate reports with Copilot in Power BI
•   Get your data ready for AI usage in Power BI

Learning Path 2: Prepare data for analysis with Power BI
You’ll learn how to use Power Query to extract data from different data sources, choose a storage mode, and connectivity type. You’ll also learn to profile, clean, and load data into Power BI before you model your data.

Module 1: Get data in Power BI
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
•   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 – Get data in Power BI

Module 2: Clean, transform, and load data in Power BI
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
•   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

Module 3: Choose a Power BI model framework
Describe model frameworks, their benefits and limitations, and features to help optimize your Power BI data models.
Lessons
•   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

Learning Path 3: Model data with Power BI
Data modeling configures and shapes your prepared data to design a semantic model with the necessary relationships and calculations using Data Analysis Expressions (DAX). This process ensures accurate analysis and sets you up to create clear, impactful Power BI reports.

Module 1: Configure a semantic model
Semantic models organize complex data into an intuitive structure, enhancing data visualization and enabling efficient, insightful reporting for better decision-making.
Lessons
•   Configure relationships
•   Configure tables
•   Configure columns
•   Configure hierarchies
•   Configure measures
•   Configure parameters
Exercise – Configure a semantic model in Power BI Desktop

Module 2: Write DAX formulas for semantic models
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
•   Understand DAX calculation types
•   Write DAX formulas
•   DAX data types
•   Work with DAX functions
•   Use DAX operators
•   Use DAX variables

Module 3: Create DAX calculations in semantic models
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
•   Create calculated tables
•   Create calculated columns
•   Understand implicit measures
•   Create explicit measures
•   Use iterator functions
Exercise – Create DAX calculations

Module 4: Modify DAX filter context in semantic models
Modifying the filter context in DAX lets you control how calculations evaluate data in Power BI semantic models. Gain deeper insights and tailor your analysis in your reports by choosing exactly what data is included in calculations.
Lessons
•   Understand filter context
•   Modify filter context
•   Use filter modifier functions
•   Examine filter context
•   Perform context transition
Exercise – Modify DAX filter context

Module 5: Use DAX time intelligence functions in semantic models
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
•   Use DAX time intelligence functions
•   Additional time intelligence calculations
Exercise – Use time intelligence functions

Module 6: Create visual calculations in Power BI Desktop
Calculations in Power BI are necessary to enrich data analysis. Visual calculations simplify complex formulas, enhance performance, and reduce maintenance.
Lessons
•   Understand visual calculations
•   Create visual calculations
•   Use parameters in visual calculations
Exercise – Create visual calculations in Power BI Desktop

Module 7: Optimize a model for performance in Power BI
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
•   Describe semantic model optimization techniques
•   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

Learning Path 4: Design effective reports in Power BI
Use data visualization and storytelling techniques to create insightful, dynamic Power BI reports that engage users, highlight key findings, and help inform decisions based on data.

Module 1: Scope report design requirements
Identify your audience, choose suitable report types, and define interface and experience requirements to effectively plan your report design.
Lessons
•   Identify the audience
•   Determine report types
•   Define user interface requirements
•   Define user experience requirements
•   Explore designs in a Power BI report

Module 2: Design Power BI reports
Design effective Power BI reports that are visually appealing and easy to understand with consistent report structure, interactive objects, and filtering.
Lessons
•   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

Module 3: Enhance Power BI report designs for the user experience
Design reports with intuitive navigation and enable users to explore data in an easy way that is meaningful to them.
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

Module 4: Perform analytics in Power BI
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
•   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 analytics in Power BI

Learning Path 5: Manage and secure Power BI
Ensure content is accessible and distributed effectively in Power BI to foster collaboration and informed decision-making. Protect sensitive information with robust security, building trust across your organization.

Module 1: Manage workspaces in Power BI service
Explore the Power BI service, create and manage workspaces, and distribute reports to users.
Lessons
•   Understand Power BI service
•   Understand workspaces
•   Publish to Power BI service

Module 2: Manage semantic models in Power BI
Semantic models are the foundation for report development in Power BI. Efficient management ensures data connectivity and improves report performance and accuracy.
Lessons
•   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

Module 3: Choose a content distribution method
Choose a content distribution method for Power BI.
Lessons
•   Understand sharing models
•   Create a Power BI app
•   Apply data governance principles
•   Track report or dashboard usage

Module 4: Create dashboards in Power BI
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
•   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 dashboards in Power BI

Module 5: Secure data access in Power BI
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
•   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