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.

Identifying Features of the Snowflake Schema

Data Ingestion and Semantic Models with Microsoft Fabric

Exercício interativo prático