Model data with Power BI
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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.
This learning path can help you prepare for the Microsoft Certified: Data Analyst Associate certification.
Prerequisites
Before you start this learning path, you should be familiar with the Power BI Desktop application. You should also have a basic understanding of data analysis concepts and terminology, such as tables, relationships, and calculations.
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Modules in this learning path
Semantic models organize complex data into an intuitive structure, enhancing data visualization and enabling efficient, insightful reporting for better decision-making.
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.
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.
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.
Calculations in Power BI are necessary to enrich data analysis. Visual calculations simplify complex formulas, enhance performance, and reduce maintenance.
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.