Duration: 1-Day Course Code: DP-601 Course Delivery: Virtual (1-Day) PST/Virtual (1-Day) GMT Level: Beginner
Course Overview
Audience Profile
Course Objectives
In this course, you will learn how to implement data lakehouses with Microsoft Fabric. You will:
• Understand the foundation of data engineering on Fabric through the exploration of the Lakehouse.
• Explore the powerful capabilities of Apache Spark for distributed data processing.
• Gain essential techniques for efficient data management, versioning, and reliability by working with Delta Lake tables.
• Explore data ingestion and orchestration using Dataflows Gen2 and Data Factory pipelines.
Prerequisites
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.
Lessons
• Introduction • Explore end-to-end analytics with Microsoft Fabric • Data teams and Microsoft Fabric • Enable and use Microsoft Fabric
After completing this module, students will be able to:
• Describe end-to-end analytics in Microsoft Fabric
Module 2: Get started with lakehouses in Microsoft Fabric+
This module details how 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 and ingest data with a Microsoft Fabric • lakehouse
After completing this module, students will be able to: • Describe core features and capabilities of lakehouses in • Microsoft Fabric • Create a lakehouse • Ingest data into files and tables in a lakehouse • Query lakehouse tables with SQL
Module 3: Use Apache Spark in Microsoft Fabric+
Apache Spark is a core technology for large-scale data analytics. in this module learn how 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
• Configure Spark in a Microsoft Fabric workspace • Identify suitable scenarios for Spark notebooks and Spark jobs • Use Spark dataframes to analyze and transform data • Use Spark SQL to query data in tables and views • Visualize data in a Spark notebook
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 • Work with delta tables in Spark • Use delta tables with streaming data • Exercise - Use delta tables in Apache Spark
• Understand Delta Lake and delta tables in Microsoft Fabric • Create and manage delta tables using Spark • Use Spark to query and transform data in delta tables • Use delta tables with Spark structured streaming
Module 5: Ingest Data with Dataflows Gen2 in Microsoft Fabric+
Data ingestion is crucial in analytics. In this module learn how 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
• Describe Dataflow capabilities in Microsoft Fabric • Create Dataflow solutions to ingest and transform data • Include a Dataflow in a pipeline
Module 6: Use Data Factory pipelines in Microsoft Fabric+
Microsoft Fabric includes Data Factory capabilities. In this module learn how 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 After completing this module, students will be able to:
• Describe pipeline capabilities in Microsoft Fabric • Use the Copy Data activity in a pipeline • Create pipelines based on predefined templates • Run and monitor pipelines
Module 7: Organize a Fabric lakehouse using medallion architecture design+
In this module, 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
• Describe the principles of using the medallion architecture in data management. • Apply the medallion architecture framework within the Microsoft Fabric environment. • Analyze data stored in the lakehouse using DirectLake in Power BI. • Describe best practices for ensuring the security and governance of data stored in the medallion architecture.
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Exam Information