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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
- A solid grasp of data management fundamentals.
- Practical experience working with SQL databases.
- Foundational knowledge of cloud computing principles.
Target Audience
- Data engineers.
- Database administrators.
- Data analysts.
21 Hours
