Microsoft - Data Warehousing with Microsoft Azure Synapse Analytics
- Offered byCoursera
Data Warehousing with Microsoft Azure Synapse Analytics at Coursera Overview
Duration | 15 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Data Warehousing with Microsoft Azure Synapse Analytics at Coursera Highlights
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 5 of 10 in the Microsoft Azure Data Engineering Associate DP-203 Exam Prep Specialization
Data Warehousing with Microsoft Azure Synapse Analytics at Coursera Course details
- In this course, you will explore the tools and techniques that can be used to work with Modern Data Warehouses productively and securely within Azure Synapse Analytics. You will learn how Azure Synapse Analytics enables you to build Data Warehouses using modern architecture patterns and how the common schema is implemented in a data warehouse. You'll learn the best practices you need to adopt to load data into a data warehouse and the techniques that you can use to optimize query performance within Azure Synapse Analytics.
- This course is part of a Specialization intended for Data engineers and developers who want to demonstrate their expertise in designing and implementing data solutions that use Microsoft Azure data services for anyone interested in preparing for the Exam DP-203: Data Engineering on Microsoft Azure (beta).
- This is the fifth course in a program of 10 courses to help prepare you to take the exam so that you can have expertise in designing and implementing data solutions that use Microsoft Azure data services.
- By the end of this Specialization, you will be ready to take and sign-up for the Exam DP-203: Data Engineering on Microsoft Azure (beta).
Data Warehousing with Microsoft Azure Synapse Analytics at Coursera Curriculum
Design a Modern Data Warehouse using Azure Synapse Analytics
Introduction to the course
Describe a modern data warehouse
Define a modern data warehouse architecture
Understand data storage for a modern data warehouse
Understand file formats and structure for a modern data warehouse
Module summary
Course syllabus
How to be successful in this course
Identify modern data warehouse architecture components
Design ingestion patterns for a modern data warehouse
Prepare and transform data with Azure Synapse Analytics
Serve data for analysis with Azure Synapse Analytics
Knowledge check
Knowledge check
Test prep
Design a multidimensional schema to optimize analytical workloads
Module introduction
Design and implement a star schema
Module summary
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
Knowledge check
Test prep
Data loading and querying in Azure Synapse Analytics
Lesson introduction
Understand data load design goals
Explain load methods into Azure Synapse Analytics
Manage source data files
Manage singleton updates and concurrent access to Azure Synapse Analytics
Implement workload management
Lesson summary
Lesson introduction
Understand performance issues related to tables
Understand table distribution design
Use indexes to improve query performance
Improve query performance with materialized views
Use read committed snapshot for data consistency
Optimize common queries with result-set caching
Lesson summary
Set-up dedicated data load accounts
Implement workload management
Simplify ingestion with the Copy Activity
Understand performance issues related to tables
Use table distribution and indexes to improve performance
Create statistics to improve query performance
Knowledge check
Test prep
Knowledge check
Test prep
Integrating pools and developer tools in Azure Synapse Analytics
Lesson 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
Externalize the use of Spark pools within Azure Synapse Workspace
Lesson summary
Lesson introduction
Work with windowing functions
Work with approximate execution
Encapsulate transact-SQL logic with stored procedures
Lesson summary
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
Transfer data outside the Synapse workspace using the PySpark connector
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
Knowledge check
Knowledge check
Test prep
Manage, optimize and secure a data warehouse
Lesson introduction
Pause compute in Azure Synapse Analytics
Use Azure Advisor to review recommendations
Lesson summary
Lesson introduction
Understand column store storage details
Describe the impact of materialized views
Understand rules for minimally logged operations
Lesson summary
Lesson introduction
Understand network security options for Azure Synapse Analytics
Configure authentication
Configure authentication using keys and shared access
Manage authorization through column and row level security
Manage authorization through column and row level security - Permissions and Best practices
Implement encryption in Azure Synapse Analytics
Lesson summary
Scale compute resources in Azure Synapse Analytics
Manage workloads in Azure Synapse Analytics
Use dynamic management views to identify and troubleshoot query performance
Understand skewed data and space usage
Check for skewed data and space usage
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
Improve the execution plan of a query with a materialized view
Optimize a delete operation
Configure conditional access
Manage authorization through column and row level security
Manage sensitive data with Dynamic Data Masking
Knowledge check
Knowledge check
Knowledge check
Test prep
Practice Exam on Work with Data Warehouses using Azure Synapse Analytics
Course recap
Course summary
About the practice exam
Next steps
Course practice exam
Data Warehousing with Microsoft Azure Synapse Analytics at Coursera Admission Process
Important Dates
Other courses offered by Coursera
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