DP-600T00 - Microsoft Fabric Analytics Engineer

Course Description

This course covers methods and practices for implementing and managing enterprise-scale data analytics solutions using Microsoft Fabric. Students will build on existing analytics experience and will learn how to use Microsoft Fabric components, including lakehouses, data warehouses, notebooks, dataflows, data pipelines, and semantic models, to create and deploy analytics assets. This course is best suited for those who have the PL-300 certification or similar expertise in using Power BI for data transformation, modeling, visualization, and sharing. Also, learners should have prior experience in building and deploying data analytics solutions at the enterprise level.

Who should attend

The primary audience for this course is data professionals with experience in data modeling, extraction, and analytics. DP-600 is designed for professionals who want to use Microsoft Fabric to create and deploy enterprise-scale data analytics solutions.

Ingest Data with Dataflows Gen2 in Microsoft Fabric

Understand Dataflows (Gen2) in Microsoft Fabric Explore Dataflows (Gen2) in Microsoft Fabric Integrate Dataflows (Gen2) and Pipelines in Microsoft Fabric

Ingest data with Spark and Microsoft Fabric notebooks

Connect to data with Spark Write data into a lakehouse Consider uses for ingested data

Use Data Factory pipelines in Microsoft Fabric

Understand pipelines Use the Copy Data activity Use pipeline templates Run and monitor pipelines

Get started with lakehouses in Microsoft Fabric

Explore the Microsoft Fabric Lakehouse Work with Microsoft Fabric Lakehouses Explore and transform data in a lakehouse

Organize a Fabric lakehouse using medallion architecture design

Describe medallion architecture Implement a medallion architecture in Fabric Query and report on data in your Fabric lakehouse Considerations for managing your lakehouse

Use Apache Spark in Microsoft Fabric

Prepare to use Apache Spark Run Spark code Work with data in a Spark dataframe Work with data using Spark SQL Visualize data in a Spark notebook

Work with Delta Lake tables in Microsoft Fabric

Understand Delta Lake Create delta tables Work with delta tables in Spark Use delta tables with streaming data

Get started with data warehouses in Microsoft Fabric

Understand data warehouse fundamentals Understand data warehouses in Fabric Query and transform data Prepare data for analysis and reporting Secure and monitor your data warehouse

Load data into a Microsoft Fabric data warehouse

Explore data load strategies Use data pipelines to load a warehouse Load data using T-SQL Load and transform data with Dataflow Gen2

Query a data warehouse in Microsoft Fabric

Use the SQL query editor Explore the visual query editor Use client tools to query a warehouse

Monitor a Microsoft Fabric data warehouse

Monitor capacity metrics Monitor current activity Monitor queries

Understand scalability in Power BI

Describe the significance of scalable models Implement Power BI data modelling best practices Configure large datasets

Create Power BI model relationships

Understand model relationships Set up relationships Use DAX relationship functions Understand relationship evaluation

Use tools to optimize Power BI performance

Use Performance analyzer Troubleshoot DAX performance by using DAX Studio Optimize a data model by using Best Practice Analyzer

Enforce Power BI model security

Restrict access to Power BI model data Restrict access to Power BI model objects Apply good modeling practices


DP-600T00 - Microsoft Fabric Analytics Engineer 2024-09-17 Online