DP-601 Implementing a Lakehouse with Microsoft Fabric
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Kursdatoer er ikke helt avklart ennå, men kontakt kurs@bouvet.no for påmelding!
This course is designed to build your foundational skills in data engineering on Microsoft Fabric, focusing on the Lakehouse concept. This course will explore the powerful capabilities of Apache Spark for distributed data processing and the essential techniques for efficient data management, versioning, and reliability by working with Delta Lake tables.
This course will also explore data ingestion and orchestration using Dataflows Gen2 and Data Factory pipelines. This course includes a combination of lectures and hands-on exercises that will prepare you to work with lakehouses in Microsoft Fabric.
Target audience
The primary audience for this course is data professionals who are familiar with data modeling, extraction, and analytics. It is designed for professionals who are interested in gaining knowledge about Lakehouse architecture, the Microsoft Fabric platform, and how to enable end-to-end analytics using these technologies.
Prerequisits
You should be familiar with basic data concepts and terminology.
Kursdatoer er ikke helt avklart ennå, men kontakt kurs@bouvet.no for påmelding!
Agenda
Module 1: Introduction to end-to-end analytics using Microsoft Fabric
Describe end-to-end analytics in Microsoft Fabric
Module 2: Get started with lakehouses in Microsoft Fabric
- 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
- 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
- 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
- Describe Dataflow (Gen2) capabilities in Microsoft Fabric
- Create Dataflow (Gen2) solutions to ingest and transform data
- Include a Dataflow (Gen2) in a pipeline
Module 6: Use Data Factory pipelines in Microsoft Fabric
- Describe pipeline capabilities in Microsoft Fabric
- Use the Copy Data activity in a pipeline
- Create pipelines based on predefined templates
- Run and monitor pipelines
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