Implementing a Lakehouse with Microsoft Fabric

This learning path introduces the foundational components of implementing a data lakehouse with Microsoft Fabric.

Prerequisites

You should be familiar with basic data concepts and terminology.

Modules in this learning path

Get started with lakehouses in Microsoft Fabric

Lakehouses merge data lake storage flexibility with data warehouse analytics. Microsoft Fabric offers a lakehouse solution for comprehensive analytics on a single SaaS platform.

• Introduction
• Explore the Microsoft Fabric lakehouse
• Work with Microsoft Fabric lakehouses
• Explore and transform data in a lakehouse
• Exercise - Create a Microsoft Fabric lakehouse
• Knowledge check
• Summary

Use Apache Spark in Microsoft Fabric

Apache Spark is a core technology for large-scale data analytics. Microsoft Fabric provides support for Spark clusters, enabling you to analyze and process data in a Lakehouse at scale.

• Introduction
• Prepare to use Apache Spark
• Run Spark code
• Connect to data sources and ingest data
• Work with data in a Spark dataframe
• Work with data using Spark SQL
• Visualize data in a Spark notebook
• Exercise - Analyze data with Apache Spark
• Knowledge check
• Summary

Work with Delta Lake tables in Microsoft Fabric

Tables in a Microsoft Fabric lakehouse are based on the Delta Lake storage format commonly used in Apache Spark. By using the enhanced capabilities of delta tables, you can create advanced analytics solutions.

• Introduction
• Understand Delta Lake
• Create delta tables
• Create delta tables
• Work with delta tables in Spark
• Use delta tables with streaming data
• Exercise - Use delta tables in Apache Spark
• Knowledge check
• Summary