Work with Data Warehouses using Azure Synapse Analytics

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Free Online Course: Work with Data Warehouses using Azure Synapse Analytics provided by Microsoft Learn is a comprehensive online course, which lasts for 7-8 hours worth of material. The course is taught in English and is free of charge.

Overview
    • Module 1: Design a Modern Data Warehouse using Azure Synapse Analytics
    • In this module, you will:

      • 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
    • In this module, you will:

      • 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
    • In this module, you will:

      • 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
    • In this module, you will:

      • 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
    • After completing this module, you will be able to:

      • 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
    • In this module, you will:

      • 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
    • In this module, you will:

      • 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
    • In this module, you will:

      • 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
    • In this module, you will:

      • 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

Syllabus
    • Module 1: Design a Modern Data Warehouse using Azure Synapse Analytics
      • Introduction
      • Describe a modern data warehouse
      • Define a modern data warehouse architecture
      • Exercise - Identify modern data warehouse architecture components
      • 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
      • Knowledge check
      • Summary
    • Module 2: Design a multidimensional schema to optimize analytical workloads
      • Introduction
      • Design and implement a star schema
      • Exercise - Create a star schema
      • Design and implement a snowflake schema
      • Exercise - Create a snowflake schema
      • Design and implement a time dimension table
      • Exercise - Create and populate a time dimension table
      • Knowledge check
      • Summary
    • Module 3: Use data loading best practices in Azure Synapse Analytics
      • Introduction
      • Understand data load design goals
      • Explain load methods into Azure Synapse Analytics
      • Manage source data files
      • Manage singleton updates
      • Set-up dedicated data load accounts
      • Implement workload management
      • Exercise - implement workload management
      • Simplify ingestion with the Copy Activity
      • Knowledge check
      • Summary
    • Module 4: Optimize data warehouse query performance in Azure Synapse Analytics
      • Introduction
      • Understand performance issues related to tables
      • Exercise - Understand performance issues related to tables
      • Understand table distribution design
      • Use indexes to improve query performance
      • Exercise - Use table distribution and indexes to improve 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
      • Knowledge check
      • Summary
    • Module 5: Integrate SQL and Apache Spark pools in Azure Synapse Analytics
      • Introduction
      • 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
      • Exercise: 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 the PySpark connector
      • Knowledge check
      • Summary
    • Module 6: Understand data warehouse developer features of Azure Synapse Analytics
      • Introduction
      • Explore the development tools for Azure Synapse Analytics
      • Understand transact-SQL language capabilities for Azure Synapse Analytics
      • Work with windowing functions
      • Exercise - work with windowing functions
      • Work with approximate execution
      • Exercise - work with approximate execution
      • Work with JSON data in SQL pools
      • Encapsulate transact-SQL logic with stored procedures
      • Knowledge check
      • Summary
    • Module 7: Manage and monitor data warehouse activities in Azure Synapse Analytics
      • Introduction
      • 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
      • Knowledge check
      • Summary
    • Module 8: Analyze and optimize data warehouse storage in Azure Synapse Analytics
      • Introduction
      • Understand skewed data and space usage
      • Exercise - Check for skewed data and space usage
      • Understand column store storage details
      • Exercise - View column store storage details
      • Understand the impact of wrong choices for column data types
      • Exercise - Compare storage requirements between optimal and sub-optimal column data types
      • Describe the impact of materialized views
      • Exercise - Improve the execution plan of a query with a materialized view
      • Understand rules for minimally logged operations
      • Exercise - Optimize a delete operation
      • Knowledge check
      • Summary
    • Module 9: Secure a data warehouse in Azure Synapse Analytics
      • Introduction
      • Understand network security options for Azure Synapse Analytics
      • Configure Conditional Access
      • Configure authentication
      • Manage authorization through column and row level security
      • Exercise - Manage authorization through column and row level security
      • Manage sensitive data with Dynamic Data Masking
      • Implement encryption in Azure Synapse Analytics
      • Knowledge check
      • Summary