Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS.
This course demonstrates how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use business intelligence tools to perform analysis on your data.
Who Should Attend
- This course is intended for:
- Database architects
- Database administrators
- Database developers
- Data analysts and scientists
This course is part of the following Certifications:
We recommend that attendees of this course have the following prerequisites:
Have taken AWS Technical Essentials (or equivalent experience with AWS)
Familiarity with relational databases and database design concepts
This course is designed to teach you how to:
Discuss the core concepts of data warehousing.
Discuss the intersection between data warehousing and big data solutions.
Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud.
Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3, to contribute to the data warehousing solution.
Evaluate approaches and methodologies for designing data warehouses.
Identify data sources and determine requirements for accessing the data.
Architect the data warehouse.
Use important commands, such as COPY, UNLOAD, and VACUUM, to manage the data in the data warehouse.
Identify performance issues, optimize queries, and tune the database for better performance.
Use features and services, such as Amazon Redshift database auditing, Amazon CloudWatch, Amazon CloudTrail, and Amazon Simple Notification Service (Amazon SNS), to monitor and audit the data warehouse.
Use a business intelligence (BI) application to perform data analysis and visualization tasks against the data warehouse.
Introduction to Data Warehousing
Introduction to Amazon Redshift
Understanding Amazon Redshift Components and Resources
Launching an Amazon Redshift Cluster
Choosing a Data Warehousing Approach
Identifying Data Sources and Requirements
Architecting the Data Warehouse
Loading Data into the Data Warehouse
Optimizing Queries and Tuning Performance
Monitoring and Auditing the Data Warehouse
Maintaining the Data Warehouse
Analyzing and Visualizing Data