Work with semantic models in Microsoft Fabric
Designing reports for enterprise scale requires more than just connecting to data. Understanding semantic models and strategies for scalability and lifecycle management are key to a successful enterprise implementation. This learning path helps you prepare for the Fabric Analytics Engineer Certification.
Prerequisites
Familiarity with Microsoft Fabric: https://video2.skills-academy.com/training/paths/get-started-fabric/
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Modules in this learning path
In this module, you'll learn how to work with implicit and explicit measures. You'll start by creating simple measures, which summarize a single column or table. Then, you'll create more complex measures based on other measures in the model. Additionally, you'll learn about the similarities of, and differences between, a calculated column and a measure.
Good modeling practices lead to scalable semantic models that simplify analysis and reporting of large, complex data, enhancing Power BI reports for an optimal user experience.
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.
Use tools to develop, manage, and optimize Power BI data model and DAX query performance.
Create Power BI assets for your analytics environment for structure and consistency, such as Power BI template and project files. Reusable assets and using the XMLA endpoint support application lifecycle management, including continuous integration and deployment.
Enforce model security in Power BI using row-level security and object-level security.