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.
4 Days
€1750.00
 

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
Azure SQLAzureApache SparkLakehouseFabricMicrosoft FabricDelta LakeDataflows Gen2Data FactoryPower BI