Duração:
1 dia
Próxima Data:
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Descrição
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.
*PVP por participante. A realização do curso nas datas apresentadas está sujeita a um quórum mínimo de inscrições.
Destinatários
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.
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Área: Microsoft
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Certificação Associada: N/A
Programa:
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:
- Explore end-to-end analytics with Microsoft Fabric
- Explore data teams and Microsoft Fabric
- Enable and use Microsoft Fabric
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.
Lessons:
- Explore the Microsoft Fabric lakehouse
- Work with Microsoft Fabric lakehouses
- Explore and transform data in a lakehouse
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.
Lessons:
- 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
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.
Lessons:
- Understand Delta Lake
- Create delta tables
- Optimize delta tables
- Work with delta tables in Spark
- Use delta tables with streaming data
Module 5: Ingest Data with Dataflows Gen2 in Microsoft Fabric
Data ingestion is crucial in analytics. Microsoft Fabric's Data Factory offers Dataflows (Gen2) for visually creating multi-step data ingestion and transformation using Power Query Online.
Lessons:
- Understand Dataflows Gen2 in Microsoft Fabric
- Explore Dataflows Gen2 in Microsoft Fabric
- Integrate Dataflows Gen2 and Pipelines in Microsoft Fabric
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.
Lessons:
- Understand pipelines
- Use the Copy Data activity
- Use pipeline templates
- Run and monitor pipelines
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.
Lessons:
- Describe medallion architecture
- Implement a medallion architecture in Fabric
- Query and report on data in your Fabric lakehouse
- Considerations for managing your lakehouse
Pré-requisitos:
You should be familiar with basic data concepts and terminology.
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