Introduction to Microsoft Fabric by Microsoft Press

Explore the features of Microsoft Fabric. Topics include OneLake, data pipelines, dataflows, T-SQL commands, data management, real-time analytics, and leveraging machine learning.

Introduction

• Introduction to Microsoft Fabric

1. Get Started with Microsoft Fabric

• Learning objectives
• Understand challenges in data analytics
• Appreciate the Microsoft Fabric vision
• Enable Microsoft Fabric on an existing Power BI tenant
• Set up a new Microsoft Fabric tenant
• Choose the right Fabric license

2. Explore the Microsoft Fabric Platform

• Learning objectives
• Understand OneLake
• Organize data in a data warehouse
• Organize data in a lakehouse
• Load and transform data through pipelines and dataflows
• Analyze data with semantic models and reports
• Work with data through notebooks
• Apply advanced data science
• Implement real-time analytics
• Act on your data with Data Activator
• Monitor and manage with Purview
• Choose roles in Fabric

3. Load Data into Fabric

• Learning objectives
• Create a pipeline to load data
• Configure shortcuts
• Synchronize data with the OneLake explorer
• Use a notebook to turn files into tables

4. Load and Transform Data with Dataflows

• Learning objectives
• Create a dataflow to load data
• Use a dataflow to turn files into tables
• Transform data with dataflows

5. Manage Data with Fabric Warehouse

• Learning objectives
• Apply T-SQL to set up a warehouse
• Query data
• Create reports with the default semantic model

6. Manage Data with Fabric Lakehouse

• Learning objectives
• Set up a lakehouse
• Query the SQL analytics endpoint
• Create reports with the default semantic model
• Create a custom semantic model on lakehouse data

7. Analyze Data through Semantic Models

• Learning objectives
• Understand Direct Lake
• Create DAX measures
• Create visual reports
• Create paginated reports

8. Apply Real-Time Analytics

• Learning objectives
• Ingest streaming data in Fabric
• Configure a KQL database
• Set up a streaming semantic model
• Build real-time reports

9. Take Action through Data Activator

• Learning objectives
• Understand Data Activator
• Set up triggers

10. Apply Data Science

• Learning objectives
• Run ML experiments in Fabric
• Predict outcomes using ML models

11. Manage Fabric Usage

• Learning objectives
• Get insights through the Purview hub
• Access admin monitoring

Summary

• Summary