Work with Data Warehouses using Azure Synapse Analytics
- Offered byMicrosoft
Work with Data Warehouses using Azure Synapse Analytics at Microsoft Overview
Duration | 7 hours |
Total fee | Free |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Work with Data Warehouses using Azure Synapse Analytics at Microsoft Highlights
- Learn how to approach and implement security to protect your data with Azure Synapse Analytics
- Learn how Azure Synapse Analytics enables you to build Data Warehouses using modern architecture patterns
Work with Data Warehouses using Azure Synapse Analytics at Microsoft Course details
- Design a Modern Data Warehouse using Azure Synapse Analytics
- Design a multidimensional schema to optimize analytical workloads
- Use data loading best practices in Azure Synapse Analytics
- Optimize data warehouse query performance in Azure Synapse Analytics
- Integrate SQL and Apache Spark pools in Azure Synapse Analytics
- Understand data warehouse developer features of Azure Synapse Analytics
- Analyze and optimize data warehouse storage in Azure Synapse Analytics
- Secure a data warehouse in Azure Synapse Analytics
- Understand the common schema implemented in a data warehouse
- Know the techniques that you can use to optimize query performance within Azure Synapse Analytics
- Learn how to integrate SQL and Apache Spark pools in Azure Synapse Analytics
Work with Data Warehouses using Azure Synapse Analytics at Microsoft Curriculum
MODULE:1
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
MODULE:2
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
MODULE:3
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
Manage concurrent access to Azure Synapse Analytics
Implement workload management
Exercise - implement workload management
Simplify ingestion with the Copy Activity
MODULE:4
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
MODULE:5
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
MODULE:6
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
MODULE:7
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
MODULE:8
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
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