Database & Reporting Training / Big Data Training
Amazon Redshift Architecture and SQL
Amazon Redshift is a high performance, petabyte-scale data warehouse platform. Accelebrate's Amazon Redshift Architecture and SQL training teaches participants the basic and advanced levels of Amazon Redshift Architecture and SQL, enabling them to take full advantage of the platform's capabilities.
Location and Pricing
Most Accelebrate courses are delivered as private, customized, on-site training at our clients' locations worldwide for groups of 3 or more attendees and are custom tailored to their specific needs. Please visit our client list to see organizations for whom we have delivered private in-house training. These courses can also be delivered as live, private online classes for groups that are geographically dispersed or wish to save on the instructor's or students' travel expenses. To receive a customized proposal and price quote for private training at your site or online, please contact us.
In addition, some courses are available as live, online classes for individuals. See a schedule of online courses.
Amazon Redshift Training Objectives
All students will learn:
Amazon Redshift Training Outline
What is Columnar?
Best Practices For Table Design
The WHERE Clause
Distinct Vs Group By AND TOP
Substrings and Positioning Functions
Interrogating the Data
Set Operators Functions
Statistical Aggregate Functions
No prior experience is required.
All Amazon Redshift training students receive comprehensive courseware in electronic format.
Software needed for each student PC:
Internet access via Firefox, Chrome, or Internet Explorer is required in order to access the remote environment used for this training.
For classes delivered online, all participants need either dual monitors or a separate device logged into the online session so that they can do their work on one screen and watch the instructor on the other. A separate computer connected to a projector or large screen TV would be another way for students to see the instructor's screen simultaneously with working on their own.