Course Outline

Introduction to End-to-End Analysis with Microsoft Fabric

  • Overview of Microsoft Fabric
  • Understanding the Lakehouse Architecture
  • End-to-End Analytics Workflow

Getting Started with Lakehouses in Microsoft Fabric

  • Core Features and Capabilities of Lakehouses
  • Creating and Configuring a Lakehouse
  • Data Ingestion into Lakehouse Tables

Using Apache Spark in Microsoft Fabric

  • Configuring Apache Spark in Microsoft Fabric
  • Leveraging Spark for Distributed Data Processing
  • Analyzing and Transforming Data with Spark DataFrames

Working with Delta Lake Tables in Microsoft Fabric

  • Introduction to Delta Lake and Delta Tables
  • Managing and Versioning Data with Delta Tables
  • Implementing Data Transformations and Queries

Ingesting Data with Dataflows Gen2 in Microsoft Fabric

  • Capabilities of Dataflows Gen2
  • Designing Dataflow Solutions for Data Ingestion
  • Integrating Dataflows into Data Pipelines

Using Data Factory Pipelines in Microsoft Fabric

  • Overview of Data Factory Pipelines
  • Building and Orchestrating Data Pipelines
  • Automating Data Movements and Transformations

Summary and Next Steps

Requirements

  • An understanding of data management principles
  • Experience with SQL databases
  • Basic knowledge of cloud computing concepts

Audience

  • Data engineers
  • Database administrators
  • Data analysts
 21 Hours

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