Course Information
Schedules
- 24 Jun 2026 (Wed) - 26 Jun 2026 (Fri) 9:30 AM - 5:00 PM
Registration period
23 Jun 2026 (Tue) - 24 Jun 2026 (Wed)
Price
HKD 9,000
(Early Bird HK9000
Standard HK18000)
(Early Bird HK9000
Standard HK18000)
Course Level
Study Mode
Duration
3 Day(s)
Language
Cantonese
Location
2/F, Centre Point, 181 Gloucester Road, Wanchai, HK
Course Overview
Course description
Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloudbased 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 AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data.
- Course level: Intermediate
- Duration: 3 days
Activities
- This course includes presentations, group exercises, and hands-on labs.
Course objectives
In this course, you will:
- Discuss the core concepts of data warehousing, and 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
- Architect 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 Amazon QuickSight to perform data analysis and visualization tasks against the data
- warehouse
What You’ll Learn
Day 1
Module 1: Introduction to Data Warehousing
Relational databases
Data warehousing concepts
The intersection of data warehousing and big data
Overview of data management in AWS
Hands-on lab 1: Introduction to Amazon Redshift
Module 2: Introduction to Amazon Redshift
Conceptual overview
Real-world use cases
Hands-on lab 2: Launching an Amazon Redshift cluster
Module 3: Launching clusters
Building the cluster
Connecting to the cluster
Controlling access
Database security
Load data
Hands-on lab 3: Optimizing database schemas
Day 2
Module 4: Designing the database schema
Schemas and data types
Columnar compression
Data distribution styles
Data sorting methods
Module 5: Identifying data sources
Data sources overview
Amazon S3
Amazon DynamoDB
Amazon EMR
Amazon Kinesis Data Firehose
AWS Lambda Database Loader for Amazon Redshift
Hands-on lab 4: Loading real-time data into an Amazon Redshift database
