Microsoft Fabric Analytics Engineer
(4 days)
Course Description
This course covers methods and practices for implementing and managing enterprise-scale data analytics solutions using Microsoft Fabric. Students will learn how to use Fabric dataflows, pipelines, and notebooks to develop analytics assets such as semantic models, data warehouses, and lakehouses. This course is designed for experienced data professionals skilled at data preparation, modeling, analysis, and visualization, such as the PL-300: Power BI Data Analyst certification.
Learning Objectives
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Implement Dataflow solutions for data ingestion and transformation in Fabric, including Spark integration
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Access external data sources, configure authentication, and optimize data intake for Fabric lakehouses
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Learn techniques to load data into Fabric lakehouses as files or Delta tables
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Understand and utilize Fabric's pipeline capabilities, including the Copy Data activity and pre-built templates, to orchestrate data flows
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Design and create Fabric lakehouses, ingest data efficiently in various formats, and query data using SQL
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Apply the principles of the medallion architecture within the Fabric environment for effective data management
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Analyze data stored in Fabric lakehouses directly from Power BI using DirectLake capabilities
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Configure and utilize Spark within Fabric, choose suitable scenarios for Spark notebooks and jobs, and manipulate data through Spark data frames
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Understand and manage Delta Lake and delta tables in Fabric using Spark for efficient data management and transformations
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Differentiate data warehouses from lakehouses, work with data warehouses in Fabric, implement data loading strategies, and build pipelines using T-SQL.
Who Should Attend
The primary audience for this course is data professionals with experience in data modeling and analytics. DP-600 is designed for professionals who want to use Microsoft Fabric to create and deploy enterprise-scale data analytics solutions. Learners should have prior experience with one of the following programming languages: Structured Query Language (SQL), Kusto Query Language (KQL), or Data Analysis Expressions (DAX).
Prerequisites
- Strong data modeling skills and a solid background in Power BI.
Course Outline
Module 1: Get started with Microsoft Fabric
- Introduction to end-to-end analytics using Microsoft Fabric
- Get started with lakehouses in Microsoft Fabric
- Use Apache Spark in Microsoft Fabric
- Work with Delta Lake tables in Microsoft Fabric
- Orchestrate processes and data movement with Microsoft Fabric
- Ingest Data with Dataflows Gen2 in Microsoft Fabric
- Get started with data warehouses in Microsoft Fabric
- Get started with Real-Time Intelligence in Microsoft Fabric
- Get started with data science in Microsoft Fabric
- Administer a Microsoft Fabric environment
Module 2: Implement a data warehouse with Microsoft Fabric
- Introduction to end-to-end analytics using Microsoft Fabric
- Get started with data warehouses in Microsoft Fabric
- Load data into a Microsoft Fabric data warehouse
- Query a data warehouse in Microsoft Fabric
- Monitor a Microsoft Fabric data warehouse
- Secure a Microsoft Fabric data warehous
Module 3: Work with semantic models in Microsoft Fabric
- Create DAX calculations in semantic models
- Design scalable semantic models
- Optimize a model for performance in Power BI
- Create and manage Power BI assets
- Enforce Power BI model security
Module 4: Administer and govern Microsoft Fabric
- Administer a Microsoft Fabric environment
- Secure data access in Microsoft Fabric
- Secure a Microsoft Fabric data warehouse
- Govern data in Microsoft Fabric with Purview
