Design a Modern Data Warehouse using Azure Synapse Analytics-Welcome to the course
Introduction to the course
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Course syllabus
How to be successful in this course
Design a Modern Data Warehouse using Azure Synapse Analytics-Build a modern data warehouse
Describe a modern data warehouse
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Define a modern data warehouse architecture
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Identify modern data warehouse architecture components
Design ingestion patterns for a modern data warehouse
Design a Modern Data Warehouse using Azure Synapse Analytics-Work with data in a modern data warehouse
Understand data storage for a modern data warehouse
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Understand file formats and structure for a modern data warehouse
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Prepare and transform data with Azure Synapse Analytics
Serve data for analysis with Azure Synapse Analytics
Module summary
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Design a multidimensional schema to optimize analytical workloads-Design and implement data stores in a modern data warehouse
Module introduction
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Design and implement a star schema
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Create a star schema
Design and implement a snowflake schema
Create a snowflake schema
Design and implement a time dimension table
Create and populate a time dimension table
Module summary
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Data loading and querying in Azure Synapse Analytics-Use data loading best practices in Azure Synapse Analytics
Lesson introduction
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Understand data load design goals
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Explain load methods into Azure Synapse Analytics
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Manage source data files
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Manage singleton updates and concurrent access to Azure Synapse Analytics
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Set-up dedicated data load accounts
Implement workload management
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Implement workload management
Simplify ingestion with the Copy Activity
Lesson summary
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Data loading and querying in Azure Synapse Analytics-Optimize data warehouse query performance in Azure Synapse Analytics
Lesson introduction
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Understand performance issues related to tables
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Understand performance issues related to tables
Understand table distribution design
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Use indexes to improve query performance
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Use table distribution and indexes to improve performance
Create statistics to improve query performance
Improve query performance with materialized views
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Use read committed snapshot for data consistency
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Optimize common queries with result-set caching
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Lesson summary
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Integrating pools and developer tools in Azure Synapse Analytics-Integrate SQL and Apache Spark pools in Azure Synapse Analytics
Lesson introduction
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Describe the integration methods between SQL and Spark pools in Azure Synapse Analytics
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Understand the use-cases for SQL and Spark pools integration
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Authenticate in Azure Synapse Analytics
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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
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Transfer data outside the Synapse workspace using the PySpark connector
Lesson summary
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Integrating pools and developer tools in Azure Synapse Analytics-Understand data warehouse developer features of Azure Synapse Analytics
Lesson introduction
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Explore the development tools for Azure Synapse Analytics
Understand transact-SQL language capabilities for Azure Synapse Analytics
Work with windowing functions
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Work with windowing functions
Work with approximate execution
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Work with approximate execution
Work with JSON data in SQL pools
Encapsulate transact-SQL logic with stored procedures
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Lesson summary
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Manage, optimize and secure a data warehouse-Manage and monitor data warehouse activities in Azure Synapse Analytics
Lesson introduction
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Scale compute resources in Azure Synapse Analytics
Pause compute in Azure Synapse Analytics
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Manage workloads in Azure Synapse Analytics
Use Azure Advisor to review recommendations
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Use dynamic management views to identify and troubleshoot query performance
Lesson summary
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Manage, optimize and secure a data warehouse-Analyze and optimize data warehouse storage in Azure Synapse Analytics
Lesson introduction
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Understand skewed data and space usage
Check for skewed data and space usage
Understand column store storage details
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View column store storage details
Understand the impact of wrong choices for column data types
Compare storage requirements between optimal and sub-optimal column data types
Describe the impact of materialized views
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Improve the execution plan of a query with a materialized view
Understand rules for minimally logged operations
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Optimize a delete operation
Lesson summary
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Manage, optimize and secure a data warehouse-Secure a data warehouse in Azure Synapse Analytics
Lesson introduction
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Understand network security options for Azure Synapse Analytics
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Configure conditional access
Configure authentication
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Configure authentication using keys and shared access
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Manage authorization through column and row level security
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Manage authorization through column and row level security - Permissions and Best practices
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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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Lesson summary
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Practice Exam on Work with Data Warehouses using Azure Synapse Analytics-Course Practice Exam
Course recap
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About the practice exam
Practice Exam on Work with Data Warehouses using Azure Synapse Analytics-Course wrap up
Course summary
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Next steps