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cours

Data Ingestion and Semantic Models with Microsoft Fabric

Débutant

Updated 12/2024

Learn to bring data into Microsoft Fabric, covering Pipelines, Dataflows, Shortcuts, Semantic Models, security, and model refresh.

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AzureAutre4 heures15 vidéos57 exercices4,250 XPDéclaration de réalisation

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Description du cours

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.

Conditions préalables

Introduction to Microsoft Fabric

1

Understanding Data Factory Pipelines and Shortcuts

Commencer le chapitre

Data Ingestion and Semantic Models

Bringing Data into Fabric with Pipelines

Introduction to Fabric Data Pipelines

Exploring Data Pipeline Activities

Pipelines with Parameters and Variables

Implementing Scheduled Pipeline Run

Storage Solutions and SQL Object Creation

Ingesting Data into Lakehouse Tables and Files

Logging Execution Details with Stored Procedures

Creating a View to Monitor Pipeline Logs

Shortcuts in OneLake

Identifying Shortcut and Target Paths

Understanding Shortcut Permissions in OneLake

Tracking Updates in Shortcuts

2

Dataflows Gen2 - Implementation and Optimization

Commencer le chapitre

Introduction to Dataflows Gen2

Navigating components of Dataflows Gen 2

Selecting the Right Transformation

Performing Basic Data Transformations

Data Ingestion and Scheduling in Dataflows Gen 2

Data Destination Settings: Managed vs Manual

Choosing the Right Settings for Data Refresh

Identifying Scenarios for Append and Schema

Optimizing Dataflow Performance

Default Destinations in Dataflow Gen2

Staging in DataFlow Gen2

Evaluating Fast Copy Requirements

Choosing the Right Ingestion & Storage Solutions

Identifying the Right Data Ingestion Method

Lakehouse or Warehouse: Understanding the Limits

3

Building Semantic Models in Power BI

Commencer le chapitre

Developing Effective Reports in Power BI

Table Integration and Relationships

Building Interactive Reports with Power BI

Creating and Visualizing Measures

Classify Your DAX: Measures vs. Calculated Columns

Foundations of Semantic Models

Default vs. Custom Semantic Models

Understanding User Defined Aggregations

Understanding Large Dataset Format

Refining Relationships in Power BI Modeling

Unidirectional vs Bidirectional Relationships

Inactive vs Active Relationships

Understanding and Resolving Problematic Data Relationships

Implement Many to Many Relationship

Resolving Circular Relationships

Identifying Features of the Snowflake Schema

4

Advanced Concepts for Semantic Models

Commencer le chapitre

Enforcing Security in Power BI Semantic Models

Classifying Row-Level and Object-Level Security

Implementing Row-Level Security (RLS)

Validating Security Roles in Power BI

Managing and Optimizing Semantic Model Refreshes

Scheduled and On-Demand Model Refreshes

Semantic Model Refresh Activity

Optimize Power BI Report

Understanding Performance Analyzer

Choosing the Right Tool for Report Optimization

Identifying Data Model Issues with Tabular Editor

Understanding the Best Practice Analyzer Results

Data Ingestion and Semantic Models with Microsoft Fabric

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