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Course Outline
End-to-End Analysis Fundamentals with Microsoft Fabric
- High-level overview of Microsoft Fabric
- Exploring the Lakehouse architectural model
- The complete analytics workflow
Initial Setup of Lakehouses in Microsoft Fabric
- Key features and functionalities of Lakehouses
- Procedures for creating and configuring a Lakehouse
- Methods for ingesting data into Lakehouse tables
Integrating Apache Spark in Microsoft Fabric
- Setup and configuration of Apache Spark within Fabric
- Harnessing Spark for distributed data processing tasks
- Data analysis and transformation using Spark DataFrames
Managing Delta Lake Tables within Microsoft Fabric
- Basics of Delta Lake and Delta Tables
- Strategies for data versioning and management via Delta Tables
- Execution of data transformations and queries
Data Ingestion Strategies with Dataflows Gen2 in Microsoft Fabric
- Functional capabilities of Dataflows Gen2
- Architecting dataflow solutions for effective ingestion
- Embedding Dataflows within broader data pipelines
Leveraging Data Factory Pipelines in Microsoft Fabric
- Introduction to Data Factory pipeline mechanics
- Construction and orchestration of data pipelines
- Automation of data movement and transformation processes
Requirements
- Familiarity with fundamental data management concepts
- Practical experience with SQL databases
- Foundational understanding of cloud computing principles
Intended Audience
- Data engineers
- Database administrators
- Data analysts
21 Hours
