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Course Outline
1. Azure for the Data Engineer
- Explain the evolving landscape of data.
- Survey the services within the Azure Data Platform.
- Identify the tasks performed by a Data Engineer.
- Describe use cases for cloud computing in a Case Study.
- Revisit the evolving world of data.
- Determine the Azure Data Platform Services.
- Identify tasks to be performed by a Data Engineer.
- Finalize the data engineering deliverables.
2. Working with Data Storage
- Choose a data storage approach in Azure.
- Create an Azure Storage Account.
- Explain Azure Data Lake storage.
- Upload data into Azure Data Lake.
- Lab: Working with Data Storage.
- Choose a data storage approach in Azure.
- Create a Storage Account.
- Explain Data Lake Storage.
- Upload data into Data Lake Store.
3. Enabling Team-Based Data Science with Azure Databricks
- Explain Azure Databricks.
- Work with Azure Databricks.
- Read data with Azure Databricks.
- Perform transformations with Azure Databricks.
- Lab: Enabling Team-Based Data Science with Azure Databricks.
- Explain Azure Databricks.
- Work with Azure Databricks.
- Read data with Azure Databricks.
- Perform transformations with Azure Databricks.
4. Building Globally Distributed Databases with Cosmos DB
- Create an Azure Cosmos DB database designed to scale.
- Insert and query data in your Azure Cosmos DB database.
- Build a .NET Core app for Cosmos DB in Visual Studio Code.
- Distribute your data globally with Azure Cosmos DB.
- Lab: Building Globally Distributed Databases with Cosmos DB.
- Create an Azure Cosmos DB.
- Insert and query data in Azure Cosmos DB.
- Build a .NET Core App for Azure Cosmos DB using VS Code.
- Distribute data globally with Azure Cosmos DB.
5. Working with Relational Data Stores in the Cloud
- Use Azure SQL Database.
- Describe Azure SQL Data Warehouse.
- Create and Query an Azure SQL Data Warehouse.
- Use PolyBase to Load Data into Azure SQL Data Warehouse.
- Lab: Working with Relational Data Stores in the Cloud.
- Use Azure SQL Database.
- Describe Azure SQL Data Warehouse.
- Create and Query an Azure SQL Data Warehouse.
- Use PolyBase to Load Data into Azure SQL Data Warehouse.
6. Performing Real-Time Analytics with Stream Analytics
- Explain data streams and event processing.
- Data Ingestion with Event Hubs.
- Process Data with Stream Analytics Jobs.
- Lab: Performing Real-Time Analytics with Stream Analytics.
- Explain data streams and event processing.
- Data Ingestion with Event Hubs.
- Process Data with Stream Analytics Jobs.
7. Orchestrating Data Movement with Azure Data Factory
- Explain how Azure Data Factory works.
- Azure Data Factory Components.
- Azure Data Factory and Databricks.
- Lab: Orchestrating Data Movement with Azure Data Factory.
- Explain how Data Factory Works.
- Azure Data Factory Components.
- Azure Data Factory and Databricks.
8. Securing Azure Data Platforms
- An introduction to security.
- Key security components.
- Securing Storage Accounts and Data Lake Storage.
- Securing Data Stores.
- Securing Streaming Data.
- Lab: Securing Azure Data Platforms.
- An introduction to security.
- Key security components.
- Securing Storage Accounts and Data Lake Storage.
- Securing Data Stores.
- Securing Streaming Data.
9. Monitoring and Troubleshooting Data Storage and Processing
- Explain the monitoring capabilities that are available.
- Troubleshoot common data storage issues.
- Troubleshoot common data processing issues.
- Manage disaster recovery.
- Lab: Monitoring and Troubleshooting Data Storage and Processing.
- Explain the monitoring capabilities that are available.
- Troubleshoot common data storage issues.
- Troubleshoot common data processing issues.
- Manage disaster recovery.
Requirements
- Experience with basic data analysis (e.g., Excel).
- A general understanding of cloud concepts (e.g., AWS).
Audience
- Database engineers.
- Developers.
35 Hours
Testimonials (2)
Doing Exercise
Joe Pang - Lands Department, Hong Kong
Course - QGIS for Geographic Information System
Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
