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Duration 21 hours
Course Outline
Fundamentals of End-to-End Analytics with Microsoft Fabric
- Introduction to Microsoft Fabric
- Exploring the Lakehouse Architecture
- The Complete End-to-End Analytics Workflow
Initiating Lakehouse Implementation in Microsoft Fabric
- Key Features and Capabilities of Lakehouses
- Steps for Creating and Configuring a Lakehouse
- Processes for Ingesting Data into Lakehouse Tables
Integrating Apache Spark within Microsoft Fabric
- Setup and Configuration of Apache Spark in Microsoft Fabric
- Applying Spark for Distributed Data Processing
- Data Analysis and Transformation using Spark DataFrames
Managing Delta Lake Tables within Microsoft Fabric
- Overview of Delta Lake and Delta Tables
- Data Management and Versioning Strategies with Delta Tables
- Executing Data Transformations and Queries
Data Ingestion via Dataflows Gen2 in Microsoft Fabric
- Exploring the Capabilities of Dataflows Gen2
- Designing Dataflow Solutions for Efficient Ingestion
- Integrating Dataflows into Broader Data Pipelines
Orchestrating Pipelines with Data Factory in Microsoft Fabric
- Introduction to Data Factory Pipelines
- Constructing and Orchestrating Data Pipelines
- Automation of Data Movement and Transformation Tasks
Requirements
- Familiarity with core data management principles.
- Practical experience working with SQL databases.
- Foundational understanding of cloud computing concepts.
Intended Audience
- Data engineers.
- Database administrators.
- Data analysts.
