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Duration 21 hours (3 days)
Course Outline
Introduction to End-to-End Analytics with Microsoft Fabric
- High-level overview of Microsoft Fabric
- Deep dive into Lakehouse architecture
- Mapping the end-to-end analytics workflow
Getting Started with Lakehouses in Microsoft Fabric
- Exploring core features and capabilities of Lakehouses
- Steps for creating and configuring a Lakehouse
- Methods for ingesting data into Lakehouse tables
Leveraging Apache Spark in Microsoft Fabric
- Configuring Apache Spark within the Fabric environment
- Applying Spark for efficient distributed data processing
- Data analysis and transformation using Spark DataFrames
Managing Delta Lake Tables in Microsoft Fabric
- Foundations of Delta Lake and Delta Tables
- Techniques for data versioning and management using Delta Tables
- Executing data transformations and complex queries
Data Ingestion with Dataflows Gen2 in Microsoft Fabric
- Understanding the capabilities of Dataflows Gen2
- Designing effective dataflow solutions for ingestion
- Seamless integration of Dataflows into broader data pipelines
Orchestrating Pipelines with Data Factory in Microsoft Fabric
- Overview of Data Factory pipeline capabilities
- Constructing and orchestrating robust data pipelines
- Automation of data movements and transformations
Requirements
- Solid grasp of data management fundamentals
- Practical experience with SQL databases
- Familiarity with core cloud computing concepts
Target Audience
- Data engineers
- Database administrators
- Data analysts
