Building Data Analytics Solutions using Amazon Redshift
Course Duration
1 Day
Audience
Employees of federal, state and local governments; and businesses working with the government.
Prerequisites
Students with a minimum one-year experience managing data warehouses will benefit from this course.
Course Description
This course covers designing and operating a cloud data warehouse using Amazon Redshift. Students learn how to load, query, and optimize data in Redshift, configure clusters, manage security, and integrate Redshift with other AWS analytics services for enterprise-scale reporting and analysis.
Learning Objectives
- Compare the features and benefits of data warehouses, data lakes, and modern data architectures
- Design and implement a data warehouse analytics solution
- Identify and apply appropriate techniques, including compression, to optimize data storage
- Select and deploy appropriate options to ingest, transform, and store data
- Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case
- Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights
- Secure data at rest and in transit
- Monitor analytics workloads to identify and remediate problems
- Apply cost management best practices
Course Outline
- Module A: Overview of Data Analytics and the Data Pipeline
- Module 1: Using Amazon Redshift in the Data Analytics Pipeline
- Module 2: Introduction to Amazon Redshift
- Module 3: Ingestion and Storage
- Module 4: Processing and Optimizing Data
- Module 5: Security and Monitoring of Amazon Redshift Clusters
- Module 6: Designing Data Warehouse Analytics Solutions
- Module B: Developing Modern Data Architectures on AWS