Big Data


Intermediate, 3 Days

Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS.

We recommend that attendees of this course have the following prerequisites

  • Students should complete the AWS Technical Essentials course or have equivalent experience
  • Basic understanding of data warehousing, relational database systems, and database design

Day 1

  • Module 1: Introduction to Data Warehousing
  • Module 2: Introduction to Amazon Redshift
  • Lab: Introduction to Amazon Redshift
  • Module 3: Launching Clusters
  • Lab: Launching an Amazon Redshift Cluster

Day 2

  • Module 4: Designing the Database Schema
  • Lab: Optimizing Database Schemas
  • Module 5: Identifying Data Sources
  • Lab: Loading Real-Time Data into Your Amazon Redshift Database
  • Module 6: Loading DataR
  • Lab: Loading Data with the COPY Command

Day 3

  • Module 7: Writing Queries and Tuning Performance
  • Lab: Configuring Workload Management
  • Module 8: Amazon Redshift Spectrum
  • Lab: Using Amazon Redshift Spectrum
  • Module 9: Maintaining Clusters
  • Lab: Auditing and Monitoring Amazon Redshift Clusters
  • Lab: Backing Up, Restoring and Resizing Clusters
  • Module 10: Analyzing and Visualizing Data
  • Course Wrap-Up

This course teaches you how to:

  • Discuss the core concepts of data warehousing
  • Discuss 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
  • Evaluate approaches and methodologies for designing data warehouses
  • Identify data sources and determine requirements for accessing the data
  • Architect the data warehouse. Use important commands, such as COPY, UNLOAD, and VACUUM, to manage the data in 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 features and services, such as Amazon Redshift database auditing, Amazon CloudWatch, Amazon CloudTrail, and Amazon Simple Notification Service (Amazon SNS), to monitor and audit the data warehouse
  • Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse

This course is part of the following Certifications:

  • AWS Certified Database – Specialty
AWS database specialty shield

This course will be delivered through a mix of:

  • Instructor-led discussion & demonstrations
  • Web-based video, and hands-on lab exercises

The fee for this course is $2,050.00.

Cal Poly Alumni are eligible for a 10% discount.

California businesses may qualify for additional support via funding from the Employment Training Panel (ETP). The ETP discount is up to 50% off AWS training courses for your employees. To learn more and determine whether your company qualifies for ETP funding, please fill out the inquiry form.

About Data warehousing on AWS

male tech inserting a new server rack into a cabinet in a data center

In this course, we demonstrate how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, we demonstrate how to use Amazon QuickSight to perform analysis on your data.

Cal Poly is an AWS Academy Institution with authorized Academy instructors as well as the first university in the world to be an AWS Authorized Training Partner.

Who Should Attend

This course is intended for:

Individuals responsible for designing and implementing databases, namely Database Architects, Database Administrators and Database Developers.
Data Scientists and Data Analysts interested in learning about data warehousing on AWS