Length: 3 Days
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
We recommend that attendees of this course have the following prerequisites:
- Courses taken: AWS Technical Essentials (or equivalent experience with AWS)
- Familiarity with relational databases and database design concepts
WHAT YOU’LL LEARN
This course teaches 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 Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket.
- 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 Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse.
WHO SHOULD ATTEND
This course is intended for:
- Database architects
- Database administrators
- Database developers
- Data analysts and scientists
This course covers the following concepts:
- Course Introduction
- 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