DP-600T00 Microsoft Fabric Analytics Engineer
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.
Agenda
- Understand Dataflows (Gen2) in Microsoft Fabric
- Explore Dataflows (Gen2) in Microsoft Fabric
- Integrate Dataflows (Gen2) and Pipelines in Microsoft Fabric
- Connect to data with Spark
- Write data into a lakehouse
- Consider uses for ingested data
- Understand pipelines
- Use the Copy Data activity
- Use pipeline templates
- Run and monitor pipelines
- Explore the Microsoft Fabric Lakehouse
- Work with Microsoft Fabric Lakehouses
- Explore and transform data in a lakehouse
- Describe medallion architecture
- Implement a medallion architecture in Fabric
- Query and report on data in your Fabric lakehouse
- Considerations for managing your lakehouse
- 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
- Understand Delta Lake
- Create delta tables
- Work with delta tables in Spark
- Use delta tables with streaming data
- 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
- Explore data load strategies
- Use data pipelines to load a warehouse
- Load data using T-SQL
- Load and transform data with Dataflow Gen2
- Use the SQL query editor
- Explore the visual query editor
- Use client tools to query a warehouse
- Monitor capacity metrics
- Monitor current activity
- Monitor queries
- Describe the significance of scalable models
- Implement Power BI data modeling best practices
- Configure large datasets
- Understand model relationships
- Set up relationships
- Use DAX relationship functions
- Understand relationship evaluation
- Use Performance analyzer
- Troubleshoot DAX performance by using DAX Studio
- Optimize a data model by using Best Practice Analyzer
- Restrict access to Power BI model data
- Restrict access to Power BI model objects
- Apply good modeling practices
FREE
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Course Type: Instructor Led