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Duration 21 hours
Course Outline
Introduction to End-to-End Analysis with Microsoft Fabric
- Overview of the Microsoft Fabric ecosystem
- Insight into the Lakehouse architectural model
- End-to-end analytics workflow dynamics
Getting Started with Lakehouses in Microsoft Fabric
- Key features and capabilities of Lakehouses
- Steps for creating and configuring a Lakehouse
- Processes for ingesting data into Lakehouse tables
Using Apache Spark in Microsoft Fabric
- Configuration of Apache Spark within Microsoft Fabric
- Harnessing Spark for distributed data processing
- Data analysis and transformation using Spark DataFrames
Working with Delta Lake Tables in Microsoft Fabric
- Basics of Delta Lake and Delta table structures
- Data management and versioning via Delta tables
- Executing data transformations and complex queries
Ingesting Data with Dataflows Gen2 in Microsoft Fabric
- Functional capabilities of Dataflows Gen2
- Architecting Dataflow solutions for data ingestion
- Embedding Dataflows within broader data pipelines
Using Data Factory Pipelines in Microsoft Fabric
- Introduction to Data Factory pipeline concepts
- Construction and orchestration of data pipelines
- Automation of data movement and transformation tasks
Requirements
- Familiarity with fundamental data management principles
- Practical experience with SQL databases
- A foundational grasp of cloud computing concepts
Target Audience
- Data engineers
- Database administrators
- Data analysts
