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Data Ingestion and Semantic Models with Microsoft Fabric
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Updated 12/2024Start course for free
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AzureOther4 hours15 videos57 exercises4,250 XPStatement of Accomplishment
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Course Description
Data Ingestion and Semantic Models
In this course, you’ll learn several different methods to bring data into Microsoft Fabric. After ingesting your data, you’ll then learn how to structure this data using Semantic Models to improve your visualizations and reports.Master Pipelines and Dataflows for Data Ingestion
Begin by exploring Pipelines and Dataflows in Fabric. You’ll learn to configure pipeline activities, use parameters and variables, and schedule your pipeline runs. Then, you’ll learn to use Dataflows to discover various transformation options and optimize performance with partitioning, staging, and fast copy.Leverage Shortcuts for Efficient Data Access
Learn to use different types of Shortcuts to manage deletion scenarios and enhance data accessibility through security features.Build and Optimize Semantic Models
In the second half of the course, you’ll create robust Semantic Models in Fabric. You will learn about key storage modes—Import, DirectQuery, Direct Lake, and Composite models. You’ll build effective relationships, master star and snowflake schemas, and work with large datasets to ensure optimal performance in complex scenarios.Master Advanced Concepts in Semantic Models and Power BI
Finally, you’ll learn advanced concepts for managing and optimizing semantic models. You’ll implement Row-Level Security (RLS) and Object-Level Security (OLS), refresh models, and develop comprehensive Power BI reports. Then, within Power BI, you’ll explore Copilot, optimize performance with DAX Studio, and leverage tools like Tabular Editor’s Best Practice Analyzer (BPA) and Performance Analyzer to create efficient, secure models and reports.Prerequisites
Introduction to Microsoft Fabric1
Understanding Data Factory Pipelines and Shortcuts
2
Dataflows Gen2 - Implementation and Optimization
3
Building Semantic Models in Power BI
4
Advanced Concepts for Semantic Models
Data Ingestion and Semantic Models with Microsoft Fabric
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