What you’ll learn
In this course, participants will learn how to:
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, optimise queries, and tune the database for better performance
Use Amazon Redshift Spectrum to analyse data directly from an Amazon S3 bucket
Use Amazon QuickSight to perform data analysis and visualisation tasks against the data warehouse
AWS at DDLS
DDLS is an official AWS Training Partner for the Australian and Philippines region. Through our Authorised AWS Instructors, we can provide you with a learning path that’s relevant to you and your organisation, so you can get more out of the cloud. We offer virtual and face-to-face classroom-based training to help you build your cloud skills and enable you to achieve industry-recognised AWS Certification.
Stay ahead of the technology curve
Don’t let your tech outpace the skills of your people
Quality instructors and content
Expert instructors with real world experience and the latest vendor- approved in-depth course content.
Chosen and awarded by the world’s leading vendors as preferred training partner.
Ahead of the technology curve
No matter your chosen technologies or platforms, we can help you stay one step ahead.
Who is the course for?
This course is intended for:
We can also deliver and customise this training course for larger groups – saving your organisation time, money and resources. For more information, please contact us on 1800 853 276.
Module 1: Introduction to Data Warehousing
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
Module 3: Launching clusters
Module 4: Designing the database schema
Schemas and data types
Data distribution styles
Data sorting methods
Module 5: Identifying data sources
Data sources overview
Amazon Kinesis Data Firehose
AWS Lambda Database Loader for Amazon Redshift
Hands-on lab 4: Loading real-time data into an Amazon Redshift database
Module 6: Loading data
Loading data using COPY
Concurrent write operations
Troubleshooting load issues
Hands-on lab 5: Loading data with the COPY command
Module 7: Writing queries and tuning for performance
Amazon Redshift SQL
User-Defined Functions (UDFs)
Factors that affect query performance
The EXPLAIN command and query plans
Workload Management (WLM)
Hands-on lab 6: Configuring workload management
Module 8: Amazon Redshift Spectrum
Amazon Redshift Spectrum
Configuring data for Amazon Redshift Spectrum
Amazon Redshift Spectrum Queries
Hands-on lab 7: Using Amazon Redshift Spectrum
Module 9: Maintaining clusters
Events and notifications
Lab 8: Auditing and monitoring clusters
Backing up and restoring clusters
Resource tagging and limits and constraints
Hands-on lab 9: Backing up, restoring and resizing clusters
Module 10: Analysing and visualising data
Please Note: This is an emerging technology course. Course outline is subject to change as needed.
We recommend that attendees of this course have the following prerequisites:
Terms & Conditions
The supply of this course by DDLS is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.