- Module 1: Design a Modern Data Warehouse using Azure Synapse Analytics
- Describe a Modern Data Warehouse
- Define a Modern Data Warehouse Architecture
- Design ingestion patterns for a Modern Data Warehouse
- Understand data storage for a Modern Data Warehouse
- Understand file formats and structure for a modern data warehouse
- Prepare and transform data with Azure Synapse Analytics
- Serve data for analysis with Azure Synapse Analytics
- Module 2: Design a multidimensional schema to optimize analytical workloads
- Design and implement a star schema
- Design and implement a snowflake schema
- Design and implement a time dimension table
- Module 3: Use data loading best practices in Azure Synapse Analytics
- Understand data loading design goals
- Explain loading methods into Azure Synapse Analytics
- Manage source data files
- Manage singleton updates
- Set-up dedicated data loading accounts
- Manage concurrent access to Azure Synapse Analytics
- Implement Workload Management
- Simplify ingestion with the Copy Activity
- Module 4: Optimize data warehouse query performance in Azure Synapse Analytics
- Understand performance issues related to tables
- Understand table distribution design
- Use indexes to improve query performance
- Create statistics to improve query performance
- Improve query performance with Materialized Views
- Use read committed snapshot for data consistency
- Optimize common queries with result-set caching
- Module 5: Integrate SQL and Apache Spark pools in Azure Synapse Analytics
- Describe the integration methods between SQL and Spark Pools in Azure Synapse Analytics
- Understand the use-cases for SQL and Spark Pools integration
- Authenticate in Azure Synapse Analytics
- Transfer data between SQL and Spark Pool in Azure Synapse Analytics
- Authenticate between Spark and SQL Pool in Azure Synapse Analytics
- Integrate SQL and Spark Pools in Azure Synapse Analytics
- Externalize the use of Spark Pools within Azure Synapse workspace
- Transfer data outside the Synapse workspace using SQL Authentication
- Transfer data outside the Synapse workspace using the PySpark Connector
- Transform data in Apache Spark and write back to SQL Pool in Azure Synapse Analytics
- Module 6: Understand data warehouse developer features of Azure Synapse Analytics
- Explore the development tools for Azure Synapse Analytics
- Understand Transact-SQL language capabilities for Azure Synapse Analytics
- Work with Windowing functions
- Work with approximate execution
- Work with JSON data in SQL Pools
- Encapsulate Transact-SQL logic with stored procedures
- Module 7: Manage and monitor data warehouse activities in Azure Synapse Analytics
- Scale compute resources in Azure Synapse Analytics
- Pause compute in Azure Synapse Analytics
- Manage workloads in Azure Synapse Analytics
- Use Azure Advisor to review recommendations
- Use Dynamic Management Views to identify and troubleshoot query performance
- Module 8: Analyze and optimize data warehouse storage in Azure Synapse Analytics
- Understand skewed data and space usage
- Understand column store storage details
- Understand the impact of wrong choices for column data types
- Describe the impact of materialized views
- Understand rules for minimally logged operations
- Module 9: Secure a data warehouse in Azure Synapse Analytics
- Understand network security options for Azure Synapse Analytics
- Configure Conditional Access
- Configure Authentication
- Manage authorization through column and row level security
- Manage sensitive data with Dynamic Data masking
- Implement encryption in Azure Synapse Analytics
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After completing this module, you will be able to:
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