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.

This learning path can help you prepare for the Microsoft Certified: Data Analyst Associate certification.

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.

• 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 storage mode
• Get data from Azure Analysis Services
• Fix performance issues
• Resolve data import errors
• Exercise – Get 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

• 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

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 Direct Query model
• Determine when to develop a composite model
• Choose a model framework
• Module assessment

Semantic models organize complex data into an intuitive structure, enhancing data visualization and enabling efficient, insightful reporting for better decision-making.

• Introduction
• Configure relationships
• Configure tables
• Configure columns
• Configure hierarchies
• Configure measures
• Configure parameters
• Exercise – Configure a semantic model in Power BI Desktop

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.

• Introduction
• Understand DAX calculation types
• Write DAX formulas
• 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.

• Introduction
• Create calculated tables
• Create calculated columns
• Understand implicit measures
• Create explicit measures
• Use iterator functions
• Exercise – Create DAX calculations

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.

• Introduction
• Understand filter context
• Modify filter context
• Use filter modifier functions
• Examine filter context
• Perform context transition
• Exercise – Modify DAX filter context

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.

• Introduction
• Use DAX time intelligence functions
• Additional time intelligence calculations
• Exercise – Use time intelligence functions

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
• Module assessment

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
• Describe semantic model optimization techniques
• Review performance of measures, relationships, and visuals
• Use variables to improve performance and troubleshooting
• Reduce cardinality
• Optimize Direct Query 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 designs in a Power BI report

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

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

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 analyse your data effectively.

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 analytics in Power BI

In this module you will learn the concepts of managing Power BI assets, including datasets and workspaces. You will also publish datasets to the Power BI service, then refresh and secure them.

Lessons

• Introduction
• Understand Power BI service
• Understand workspaces
• Publish to 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.

• 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

Choose a content distribution method for Power BI.

• Introduction
• Understand sharing models
• Create a Power BI app
• Apply data governance principles
• Track report or dashboard usage

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.

• 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 dashboards 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.

• Introduction
• Configure row-level security with the static method
• Configure row-level security with the dynamic method
• Use single sign-on (SSO) for Direct Query sources
• Restrict access to Power BI model objects
• Exercise – Enforce row-level security in Power BI