DP-203T00 Data Engineering On Microsoft Azure

Length: 4 Day(s), Price: $$2,682.00 exl GST

Students will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage.

  • Gain proficiency in implementing and managing data engineering workloads on Microsoft Azure.
  • Learn to utilize Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and more.
  • Focus on common data engineering tasks including orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage.

The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure.

Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions.

Specifically completing:

  • AZ-900 – Azure Fundamentals
  • DP-900 – Microsoft Azure Data Fundamentals

 1. Introduction to data engineering on Azure

 2. Introduction to Azure Data Lake Storage Gen2

 3. Introduction to Azure Synapse Analytics

 4. Use Azure Synapse serverless SQL pool to query files in a data lake

 5. Use Azure Synapse serverless SQL pools to transform data in a data lake

 6. Create a lake database in Azure Synapse Analytics

 7. Analyze data with Apache Spark in Azure Synapse Analytics

 8. Transform data with Spark in Azure Synapse Analytics

 9. Use Delta Lake in Azure Synapse Analytics

 10. Analyze data in a relational data warehouse

 11. Load data into a relational data warehouse

 12. Build a data pipeline in Azure Synapse Analytics

 13. Use Spark Notebooks in an Azure Synapse Pipeline

 14. Plan hybrid transactional and analytical processing using Azure Synapse Analytics

 15. Implement Azure Synapse Link with Azure Cosmos DB

 16. Implement Azure Synapse Link for SQL

 17. Get started with Azure Stream Analytics

 18. Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics

 19. Visualize real-time data with Azure Stream Analytics and Power BI

 20. Introduction to Microsoft Purview

 21. Integrate Microsoft Purview and Azure Synapse Analytics

 22. Explore Azure Databricks

 23. Use Apache Spark in Azure Databricks

 24. Run Azure Databricks Notebooks with Azure Data Factory

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