Design and Manage Analytics Solutions Using Power BI

Course Outline
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 will explore the different roles in data and learn the different 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.

Module 3: Get 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.

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.

Module 5: 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.

Module 6: Clean, transform, and load data in Power BI
Power Query has an incredible amount of features that are dedicated to helping you clean and prepare your data for analysis. 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.

Module 7: Choose a Power BI model framework
Describe model frameworks, their benefits and limitations, and features to help optimize your Power BI data models.

Module 8: 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.

Module 9: 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.

Module 10: 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.

Module 11: 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.

Module 12: 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.

Module 13: 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.

Module 14: Scope report design requirements
Identify your audience, choose suitable report types, and define interface and experience requirements to effectively plan your report design.

Module 15: 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.

Module 16: 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.

Module 17: 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.