DP-601T00 | 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.

Role
Data Analyst
Data Engineer
Data Scientist

Course Outline
Module 1: Introduction to end-to-end analytics using Microsoft Fabric
Discover how Microsoft Fabric can meet your enterprise's analytics needs in one platform. Learn about Microsoft Fabric, how it works, and identify how you can use it for your analytics needs.
Introduction
Explore end-to-end analytics with Microsoft Fabric
Explore data teams and Microsoft Fabric
Enable and use Microsoft Fabric
Module assessment
Summary
Module 2: 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
Module assessment
Summary
Module 3: 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
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
Module assessment
Summary
Module 4: 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
Optimize delta tables
Work with delta tables in Spark
Use delta tables with streaming data
Exercise - Use delta tables in Apache Spark
Module assessment
Summary
Module 5: Ingest Data with Dataflows Gen2 in Microsoft Fabric
Data ingestion is crucial in analytics. Microsoft Fabric's Data Factory offers Dataflows for visually creating multi-step data ingestion and transformation using Power Query Online.
Introduction
Understand Dataflows Gen2 in Microsoft Fabric
Explore Dataflows Gen2 in Microsoft Fabric
Integrate Dataflows Gen2 and Pipelines in Microsoft Fabric
Exercise - Create and use a Dataflow Gen2 in Microsoft Fabric
Module assessment
Summary
Module 6: Orchestrate processes and data movement with Microsoft Fabric
Microsoft Fabric includes Data Factory capabilities, including the ability to create pipelines that orchestrate data ingestion and transformation tasks.
Introduction
Understand pipelines
Use the Copy Data activity
Use pipeline templates
Run and monitor pipelines
Exercise - Ingest data with a pipeline
Module assessment
Summary
Module 7: Organize a Fabric lakehouse using medallion architecture design
Explore the potential of the medallion architecture design in Microsoft Fabric. Organize and transform your data across Bronze, Silver, and Gold layers of a lakehouse for optimized analytics.
Introduction
Describe medallion architecture
Implement a medallion architecture in Fabric
Query and report on data in your Fabric lakehouse
Considerations for managing your lakehouse
Exercise - Organize your Fabric lakehouse using a medallion architecture
Module assessment
Summary
 
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