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Duration 21 hours
Course Outline
Foundations of End-to-End Analytics with Microsoft Fabric
- Broad overview of the Microsoft Fabric ecosystem
- Analysis of Lakehouse architectural design
- Mapping the full analytics workflow from start to finish
Initiating Lakehouse Operations in Microsoft Fabric
- Exploring the primary features and functionalities of Lakehouses
- Steps to instantiate and configure a new Lakehouse
- Processes for loading data into Lakehouse tables
Integrating Apache Spark within Microsoft Fabric
- Setup and configuration of Apache Spark environments
- Applying Spark for large-scale distributed data processing
- Performing data analysis and reshaping using Spark DataFrames
Managing Delta Lake Tables in the Fabric Ecosystem
- Basics of Delta Lake technology and Delta table structures
- Techniques for data versioning and management using Delta tables
- Executing complex data transformations and queries
Data Ingestion Strategies with Dataflows Gen2
- Reviewing the capabilities and scope of Dataflows Gen2
- Architecting dataflow solutions for efficient ingestion
- Embedding Dataflows seamlessly into broader data pipelines
Orchestrating Workflows with Data Factory in Fabric
- Introduction to Data Factory pipeline mechanics
- Construction and coordination of automated data pipelines
- Automation of data movement and transformation tasks
Requirements
- Familiarity with fundamental data management concepts
- Practical experience working with SQL databases
- Fundamental understanding of cloud computing principles
Target Audience
- Data engineers
- Database administrators
- Data analysts
