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Course Outline
Foundations of End-to-End Analytics with Microsoft Fabric
- Brief overview of the Microsoft Fabric platform
- Exploring the Lakehouse architecture
- The complete analytics workflow process
Initiating Lakehouse Projects in Microsoft Fabric
- Key features and capabilities of Lakehouses
- Steps for creating and configuring a Lakehouse
- Methods for ingesting data into Lakehouse tables
Integrating Apache Spark within Microsoft Fabric
- Setting up Apache Spark in the Microsoft Fabric environment
- Utilizing Spark for high-performance distributed processing
- Data analysis and transformation using Spark DataFrames
Managing Delta Lake Tables in Microsoft Fabric
- Basics of Delta Lake and Delta Tables
- Techniques for data versioning and management via Delta Tables
- Executing data transformations and complex queries
Data Ingestion Strategies with Dataflows Gen2 in Microsoft Fabric
- Review of Dataflows Gen2 capabilities
- Designing effective solutions for data ingestion
- Seamless integration of Dataflows into broader data pipelines
Orchestrating Workflows with Data Factory in Microsoft Fabric
- Overview of Data Factory pipeline structures
- Construction and orchestration of data pipelines
- Automation of data movement and transformation processes
Requirements
- Familiarity with fundamental data management principles
- Practical experience working with SQL databases
- A basic grasp of cloud computing concepts
Target Audience
- Data engineers
- Database administrators
- Data analysts
21 Hours
