Data Warehousing on AWS
- Course Code GK4375
- Duration 3 days
Course Delivery
Additional Payment Options
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GTC 30 inc. VAT
GTC, Global Knowledge Training Credit, please contact Global Knowledge for more details
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Course Delivery
This course is available in the following formats:
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Company Event
Event at company
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Public Classroom
Traditional Classroom Learning
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Virtual Learning
Learning that is virtual
Request this course in a different delivery format.
Course Overview
TopCompany Events
These events can be delivered exclusively for your company at our locations or yours, specifically for your delegates and your needs. The Company Events can be tailored or standard course deliveries.
Course Schedule
TopTarget Audience
TopThis course is intended for:
- Database architects
- Database administrators
- Database developers
- Data analysts and scientists
Course Objectives
TopThis course teaches you how to:
- Discuss the core concepts of data warehousing.
- Evaluate the relationship between Amazon Redshift and other big data systems.
- Evaluate use cases for data warehousing workloads and review case studies that demonstrate implementation of AWS data and analytic services as part of a data warehousing solution.
- Choose an appropriate Amazon Redshift node type and size for your data needs.
- Discuss security features as they pertain to Amazon Redshift, such as encryption, IAM permissions, and database permissions.
- 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 Firehose, and Amazon S3, to contribute to the data warehousing solution.
- Evaluate approaches and methodologies for designing data warehouses.
- Identify data sources and assess requirements that affect the data warehouse design.
- Design the data warehouse to make effective use of compression, data distribution, and sort methods.
- Load and unload data and perform data maintenance tasks.
- Write queries and evaluate query plans to optimize query performance.
- Configure the database to allocate resources such as memory to query queues and define criteria to route certain types of queries to your configured query queues for improved processing.
- Use features and services, such as Amazon Redshift database audit logging, Amazon CloudTrail, Amazon CloudWatch, and Amazon Simple Notification Service (Amazon SNS), to audit, monitor, and receive event notifications about activities in the data warehouse.
- Prepare for operational tasks, such as resizing Amazon Redshift clusters and using snapshots to back up and restore clusters.
- Use a business intelligence (BI) application to perform data analysis and visualization tasks against your data.
Course Content
TopThis course covers the following concepts:
Day 1
- Course Introduction
- Introduction to Data Warehousing
- Introduction to Amazon Redshift
- Understanding Amazon Redshift Components and Resources
- Launching an Amazon Redshift Cluster
Day 2
- Reviewing Data Warehousing Approaches
- Identifying Data Sources and Requirements
- Designing the Data Warehouse
- Loading Data into the Data Warehouse
Day 3
- Writing Queries and Tuning Performance
- Maintaining the Data Warehouse
- Analyzing and Visualizing Data
- Course Summary
Course Prerequisites
TopWe 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
- GK4375
- Data Warehousing on AWS
- Cloud Computing
- GK4375 | Data Warehousing on AWS | Training Course | Amazon Web Services.
- Amazon Web Services