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Course Outline
Introduction to End-to-End Analysis with Microsoft Fabric
- Overview of the Microsoft Fabric ecosystem
- Understanding the Lakehouse architectural model
- Mapping out the end-to-end analytics workflow
Getting Started with Lakehouses in Microsoft Fabric
- Key features and capabilities of Lakehouses
- Creating and configuring a new Lakehouse
- Importing data into Lakehouse tables
Using Apache Spark in Microsoft Fabric
- Setting up Apache Spark within Microsoft Fabric
- Harnessing Spark for distributed data processing
- Performing analysis and data transformations using Spark DataFrames
Working with Delta Lake Tables in Microsoft Fabric
- Fundamentals of Delta Lake and Delta Tables
- Managing data lifecycle and versioning with Delta Tables
- Executing data transformations and complex queries
Ingesting Data with Dataflows Gen2 in Microsoft Fabric
- Exploring the capabilities of Dataflows Gen2
- Designing robust dataflow solutions for ingestion
- Integrating Dataflows into broader data pipelines
Using Data Factory Pipelines in Microsoft Fabric
- Overview of Data Factory pipeline functionality
- Constructing and orchestrating efficient data pipelines
- Automating data movement and transformation processes
Requirements
- A solid grasp of fundamental data management principles
- Practical experience with SQL databases
- Foundational knowledge of cloud computing concepts
Target Audience
- Data engineers
- Database administrators
- Data analysts
21 Hours
