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