Building Data Analytics Solutions Using Amazon Redshift

In this course, you will build a data analytics solution using Amazon Redshift, a cloud data warehouse service. The course focuses on the data collection, ingestion, cataloging, storage, and processing components of the analytics pipeline. You will learn to integrate Amazon Redshift with a data lake to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon Redshift.


In this course, you will learn to:

  • Compare the features and benefits of data warehouses, data lakes, and modern data architectures
  • Design and implement a data warehouse analytics solution
  • Identify and apply appropriate techniques, including compression, to optimize data storage
  • Select and deploy appropriate options to ingest, transform, and store data
  • Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case
  • Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights
  • Secure data at rest and in transit
  • Monitor analytics workloads to identify and remediate problems
  • Apply cost management best practices
  • This course is intended for data warehouse engineers, data platform engineers, and architects and operators who build and manage data analytics pipelines.

Students with a minimum one-year experience managing data warehouses will benefit from this course. We recommend that attendees of this course have:

  • Completed either AWS Technical Essentials or Architecting on AWS
  • Completed Building Data Lakes on AWS

Module A: Overview of Data Analytics and the Data Pipeline

Data analytics use cases

Using the data pipeline for analytics


Module 1: Using Amazon Redshift in the Data Analytics Pipeline

Why Amazon Redshift for data warehousing?

Overview of Amazon Redshift


Module 2: Introduction to Amazon Redshift

Amazon Redshift architecture

Interactive Demo 1: Touring the Amazon Redshift console

Amazon Redshift features

Practice Lab 1: Load and query data in an Amazon Redshift cluster


Module 3: Ingestion and Storage


Interactive Demo 2: Connecting your Amazon Redshift cluster using a Jupyter notebook with Data API

Data distribution and storage

Interactive Demo 3: Analyzing semi-structured data using the SUPER data type

Querying data in Amazon Redshift

Practice Lab 2: Data analytics using Amazon Redshift Spectrum


Module 4: Processing and Optimizing Data

Data transformation

Advanced querying

Practice Lab 3: Data transformation and querying in Amazon Redshift

Resource management

Interactive Demo 4: Applying mixed workload management on Amazon Redshift

Automation and optimization

Interactive demo 5: Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster


Module 5: Security and Monitoring of Amazon Redshift Clusters

Securing the Amazon Redshift cluster

Monitoring and troubleshooting Amazon Redshift clusters


Module 6: Designing Data Warehouse Analytics Solutions

Data warehouse use case review

Activity: Designing a data warehouse analytics workflow


Module B: Developing Modern Data Architectures on AWS

Modern data architectures

Why choose Cloud Wizard
  • Advanced Tier Training Partner
  • Amazon Authorised Instructors
  • Official AWS Content
  • Hands-on Labs
Class Deliverables
  • E-Content kit by AWS
  • Hands-on labs
  • Class completion certificates
  • Exam Prep sessions

Dates Available - Click on Book Now to proceed

Classroom1 daysAll DayMay 6, 202415,000
Classroom1 daysAll DayMay 20, 202415,000
Classroom1 daysAll DayJune 3, 202415,000
Classroom1 daysAll DayJune 17, 202415,000
Classroom1 daysAll DayJuly 1, 202415,000
Classroom1 daysAll DayJuly 15, 202415,000

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To enroll in this course, choose the starting date and make an online payment. Once your payment is confirmed, our team will reach out to you.

Wire Transfer, Credit Card, Debit Card, UPI & Purchase Order.

There is no minimum number of candidates required, we are happy to train 1 to 1 . With regards to the maximum number, we can accomodate 30 learners in one batch.

  1. Training Delivered by an Amazon Authorized Instructor.
  2. AWS Content E-Kit
  3. Hands-on-labs for 30 days
  4. Class attendance certificate

You will get the access to course content & lab on first day of your training session.

The course Completion Certificate will be issued to your email id within 2 weeks of completing your course.

A one-day course could be delivered over two half day sessions (4 hours a day), or a three-day course could be delivered over five days (4 hours a day)




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