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Module 1: Discover data analysis In this module, you will explore the different roles in data and learn the different tasks of a data analyst. After completing this module, students will be able to:

• Describe the roles in data
• Describe the tasks of a data analyst

Module 2: Get started building with Power BI Learn what Power BI is, including its building blocks and how they work together. After completing this module, students will be able to:

• Describe how Power BI services and applications work together
• Explore how Power BI can make your business more efficient
• Create compelling visuals and reports

Module 3: Get data in Power BI You'll learn how to retrieve data from a wide variety of data sources, including Microsoft Excel, relational databases, and NoSQL data stores. You'll also learn how to improve performance while retrieving data. After completing this module, students will be able to:

• 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

Module 4: Clean, transform, and load data in Power BI You will learn how to simplify a complicated model, change data types, rename objects, and pivot data. You will also learn how to profile columns so that you know which columns have the valuable data that you’re seeking for deeper analytics. 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

Module 5: Design a data model in Power BI In this module you will learn about the terminology and implementation of them, learn about why choosing the correct data granularity is important for performance and usability of your Power BI reports and you will learn about improving performance with your Power BI data models. After completing this module, students will be able to:

• Create common date tables
• Configure many-to-many relationships
• Resolve circular relationships
• Design star schemas

Module 6: Introduction to creating measures using DAX in Power BI Data Analysis Expressions (DAX) is a programming language that is used throughout Microsoft Power BI for creating calculated columns, measures, and custom tables. You can use DAX to solve a number of calculations and data analysis problems, which can help you create new information from data that is already in your model. After completing this module, students will be able to:

• Build quick measures
• Create calculated columns
• Use DAX to build measures
• Discover how context affects DAX measures
• Use the CALCULATE function to manipulate filters
• Implement time intelligence by using DAX

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 data model so that it runs more efficiently. Essentially, when your data model is optimized, it performs better. 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

Module 8: Work with Power BI visuals Learn how to choose from the exceptional visuals that Power BI makes available to you. Formatting visuals will direct the user’s attention to exactly where you want it, while helping to make the visual easier to read and interpret. After completing this module, students will be able to:

• Add visualization items to reports
• Choose an effective visualization
• Format and configure visualizations
• Import a custom visual
• Add an R or Python visual

Module 9: Create a data-driven story with Power BI reports Power BI helps you create vibrant, highly useful reports that form a cohesive, data-driven story. After completing this module, students will be able to:

• Design a report layout
• Add buttons, bookmarks, and selections
• Design report navigation
• Use basic interactions
• Use advanced interactions and drill through
• Configure conditional formatting
• Apply slicing, filtering, and sorting
• Publish and export reports
• Comment on reports
• Use Performance analyzer to tune reports
• Optimize reports for mobile use

Module 10: 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. After completing this module, students will be able to:

• 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

Module 11: Perform analytics in Power BI In this module you will learn how to use Power BI to perform data analytical functions, how to identify outliers in your data, how to group data together, and how to bin data for analysis. After completing this module, students will be able to:

• 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

Module 12: Work with AI visuals in Power BI This module describes the AI capabilities of Power BI. After completing this module, students will be able to:

• Use the Q&A visual
• Find important factors with the Key influencers visual
• Use the Decomposition Tree visual to break down a measure

Module 13: Create and manage workspaces in Power BI This module explains how you can share reports and datasets with your users and how to create a deployment strategy that makes sense for you and your organization. After completing this module, students will be able to:

• Distribute a report or dashboard
• Monitor usage and performance
• Recommend a development life cycle strategy
• Troubleshoot data by viewing its lineage
• Configure data protection

Module 14: Manage datasets in Power BI With Microsoft Power BI, you can build multiple reports from a single dataset, meaning that if you change the dataset, all reports will be updated with that change. Additionally, you can clean and prep data once rather than repeatedly for each report. After completing this module, students will be able to:

• Create dynamic reports with parameters
• Create what-if parameters
• 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)

Module 15: Implement row-level security In this module, you will 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. After completing this module, students will be able to:

• Configure row-level security by using a static method
• Configure row-level security by using a dynamic method

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