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Course Outline
Foundations of End-to-End Analytics in Microsoft Fabric
- Introduction to the Microsoft Fabric ecosystem
- Exploring the structure of the Lakehouse architecture
- Mapping out the full analytics workflow
Initial Setup: Launching Lakehouses in Microsoft Fabric
- Key features and capabilities of Lakehouses
- Steps to create and configure a new Lakehouse
- Methods for ingesting data into Lakehouse tables
Harnessing Apache Spark within Microsoft Fabric
- Setting up Apache Spark in the Microsoft Fabric environment
- Applying Spark for large-scale distributed data processing
- Performing data analysis and transformation via Spark DataFrames
Managing Data with Delta Lake Tables in Microsoft Fabric
- Overview of the Delta Lake format and Delta Tables
- Strategies for managing and versioning data using Delta Tables
- Executing data transformations and running complex queries
Data Ingestion Strategies with Dataflows Gen2 in Microsoft Fabric
- Capabilities and benefits of Dataflows Gen2
- Designing effective dataflow solutions for ingestion tasks
- Seamlessly integrating Dataflows into broader data pipelines
Orchestrating Workflows with Data Factory Pipelines in Microsoft Fabric
- Introduction to Data Factory pipeline capabilities
- Construction and orchestration of efficient data pipelines
- Automation of data movement and transformation processes
Requirements
- Familiarity with core data management principles
- Proficiency in working with SQL databases
- Foundational grasp of cloud computing fundamentals
Target Learners
- Data engineers
- Database administrators
- Data analysts
21 Hours
