Data Warehousing on AWS Training

Name: Data Warehousing on AWS
Price: 2025.00 USD
Availability: InStock
Rating: 4.5 (1200 reviews)

Price
$2,025.00 USD

Duration
3 Days

Delivery Methods
Virtual Instructor Led
Private Group

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Course Overview

Want to turn massive amounts of data into actionable insights? The Data Warehousing on AWS course teaches you how to design a cloud-based data warehousing solution using Amazon Redshift, AWS’s fully managed, petabyte-scale data warehouse. Through hands-on labs and real-world use cases, you’ll gain a deep understanding of how to build scalable, high-performance data warehousing solutions.

This training course walks you through the integration of AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3 to collect, store, and prepare data for the data warehouse. You’ll also learn how to perform analysis on your data using Amazon QuickSight—enabling business-ready insights from your AWS data.

Course Objectives

This Data Warehousing on AWS course equips learners with the knowledge and hands-on experience to build and manage a scalable cloud-based data warehouse. You’ll learn to launch Amazon Redshift clusters, architect efficient schemas, ingest data from sources like S3, Kinesis, and DynamoDB, and optimize performance for large-scale analytical workloads.

The course also teaches you to use Redshift Spectrum to query directly from S3 and to visualize data using Amazon QuickSight, enabling you to turn raw data into business intelligence.

Who Should Attend?

Database architects, database administrators, database developers, and data analysts & scientists

Top-rated instructors: Our crew of subject matter experts have an average instructor rating of 4.8 out of 5 across thousands of reviews.
Authorized content: We maintain more than 35 Authorized Training Partnerships with the top players in tech, ensuring your course materials contain the most relevant and up-to date information.
Interactive classroom participation: Our virtual training includes live lectures, demonstrations and virtual labs that allow you to participate in discussions with your instructor and fellow classmates to get real-time feedback.
Post Class Resources: Review your class content, catch up on any material you may have missed or perfect your new skills with access to resources after your course is complete.
Private Group Training: Let our world-class instructors deliver exclusive training courses just for your employees. Our private group training is designed to promote your team’s shared growth and skill development.
Tailored Training Solutions: Our subject matter experts can customize the class to specifically address the unique goals of your team.

What is Data Warehousing on AWS?

Data Warehousing on AWS is a hands-on training course that covers how to build and manage a data warehousing solution using Amazon Redshift and supporting AWS services. It focuses on ingestion, storage, security, and query optimization for big data analytics.

Why should I take the Data Warehousing on AWS course?

The Data Warehousing on AWS course equips you with new skills in data warehouse design, integration with AWS services, and performance tuning. It's ideal for professionals looking to modernize legacy systems or start building cloud-based data warehousing solutions on AWS.

How will the Data Warehousing on AWS course help me with optimizing query performance?

You’ll learn how to analyze and optimize Redshift queries using EXPLAIN plans, schema design best practices, and Workload Management (WLM). These are critical for improving response times and minimizing compute costs in high-demand analytics environments.

Who should take the Data Warehousing on AWS training course?

This training is tailored for database architects, database administrators, database developers, and data analysts or data engineers looking to upskill in AWS data warehousing technologies.

Does Data Warehousing on AWS include performance monitoring and disaster recovery?

Yes. Data Warehousing on AWS covers audit logging, resizing, backup strategies, resource limits, and disaster recovery techniques to ensure long-term cluster health and compliance.

Course Prerequisites

AWS Technical Essentials (or equivalent experience with AWS)
Familiarity with relational databases and database design concepts

Agenda

1. Introduction to Data Warehousing

Understand fundamental data warehousing concepts and how they align with cloud solutions. Explore the intersection of data warehousing and big data in AWS.

2. Introduction to Amazon Redshift

Overview of Redshift’s architecture and key functionality. Examine real-world use cases and how Redshift integrates with other AWS services.

3. Launching Redshift Clusters

Build and configure a Redshift cluster. Implement IAM access management, data encryption, and control user permissions.

4. Designing the Schema

Optimize table design with columnar compression, distribution styles, and sorting. Use best practices to enhance query performance and scalability.

5. Identifying and Integrating Data Sources

Connect to Amazon S3, Amazon EMR, Amazon Kinesis Firehose, and DynamoDB. Use AWS Lambda and custom ingestion methods for real-time data flows.

6. Loading and Preparing Data

Use the COPY command to ingest and prepare data for the data warehouse. Handle concurrent writes, data validation, and data processing workflows.

7. Writing Queries and Performance Tuning

Use Redshift SQL, UDFs, and the EXPLAIN command. Apply techniques for performance tuning, workload balancing, and resource optimization.

8. Amazon Redshift Spectrum

Query data directly from Amazon S3 without loading it into Redshift. Configure external schemas and run Spectrum queries for serverless analytics.

9. Maintaining Redshift Clusters

Monitor performance with CloudWatch, manage events, backups, and cluster resizing. Review disaster recovery, logging, and cluster management strategies.

10. Analyzing and Visualizing Data

Use Amazon QuickSight to create dashboards and visual reports. Compare QuickSight editions and explore its use for SQL-based analytics and business intelligence.