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Course Outline
Introduction to End-to-End Analysis with Microsoft Fabric
- High-level overview of Microsoft Fabric
- Exploring the Lakehouse architecture
- The end-to-end analytics workflow
Initiating Lakehouse Operations in Microsoft Fabric
- Key features and capabilities of Lakehouses
- Steps to create and configure a Lakehouse
- Importing data into Lakehouse tables
Integrating Apache Spark within Microsoft Fabric
- Configuration of Apache Spark in Microsoft Fabric
- Utilizing Spark for distributed data processing
- Performing data analysis and transformation with Spark DataFrames
Managing Delta Lake Tables in Microsoft Fabric
- Fundamentals of Delta Lake and Delta tables
- Handling data versioning and management with Delta tables
- Executing data transformations and queries
Data Ingestion via Dataflows Gen2 in Microsoft Fabric
- Functional capabilities of Dataflows Gen2
- Designing dataflow strategies for ingestion
- Embedding Dataflows into broader data pipelines
Leveraging Data Factory Pipelines in Microsoft Fabric
- Overview of Data Factory pipeline capabilities
- Construction and orchestration of data pipelines
- Automation of data movement and transformation tasks
Requirements
- Familiarity with core data management principles.
- Practical experience working with SQL databases.
- Foundational knowledge of cloud computing concepts.
Target Audience
- Data engineers
- Database administrators
- Data analysts
21 Hours
