Building Data Analytics Solutions Using Amazon Redshift - 1 Day ILT

Delivered by Cloud Wizard Consulting - AWS Advanced Training Partner and Select Tier Consulting Partner

Cloud Wizard Consulting has trained more than 5,000 professionals on AWS technologies. Our Authorized Instructors hold all AWS certifications, and our students achieve a 100% passing rate on related AWS exams. When you choose this course, you are learning from proven experts with deep, validated AWS expertise.

After completing this course, your team will be able to:

• Design and implement a production-ready Amazon Redshift data warehouse that integrates with your existing data lake
• Optimize query performance and storage costs so your organization delivers faster business insights at lower operational expense
• Secure sensitive data at rest and in transit, meeting enterprise compliance requirements
• Monitor and troubleshoot analytics workloads to maintain high availability and performance
• Evaluate modern data architectures and select the right combination of AWS services for your analytics pipeline

• 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 compression and optimization techniques for data storage
• Select and deploy options to ingest, transform, and store data
• Choose appropriate instance types, clusters, auto scaling, and network topology for your use case
• Understand how storage and processing decisions affect analysis and visualization
• Secure data at rest and in transit
• Monitor analytics workloads to identify and remediate problems
• Apply cost management best practices

A financial services firm processing millions of daily transactions needs to consolidate data from multiple source systems into Amazon Redshift for regulatory reporting and real-time business intelligence dashboards. In this course, you will work through a similar scenario - ingesting structured and semi-structured data, optimizing distribution keys for query performance, and integrating Redshift Spectrum to query historical data stored in Amazon S3 without additional ETL.

Module A: Overview of Data Analytics and the Data Pipeline

• Data analytics use cases and the analytics pipeline

Module 1: Using Amazon Redshift in the Data Analytics Pipeline

• Why Amazon Redshift for data warehousing
• Architecture overview and key features
• Interactive Demo: Touring the Amazon Redshift console
• Hands-on Lab: Load and query data in an Amazon Redshift cluster

Module 2: Ingestion and Storage

• Ingestion patterns and best practices
• Interactive Demo: Connecting via Jupyter notebook with Data API
• Data distribution, storage, and semi-structured data (SUPER data type)
• Hands-on Lab: Data analytics using Amazon Redshift Spectrum

Module 3: Processing and Optimizing Data

• Data transformation and advanced querying
• Hands-on Lab: Data transformation and querying in Amazon Redshift
• Resource and workload management
• Interactive Demo: Mixed workload management and cluster resizing

Module 4: Security and Monitoring

• Securing the Amazon Redshift cluster
• Monitoring and troubleshooting clusters

Module 5: Designing Data Warehouse Analytics Solutions

• Data warehouse use case review and design activity
• Modern data architectures on AWS

This course focuses on Amazon Redshift provisioned clusters and does not cover Redshift Serverless administration in depth, advanced ML model training on SageMaker, or migration tooling for on-premises data warehouse platforms. Participants seeking those topics should explore complementary AWS courses.

• Data warehouse engineers
• Data platform engineers
• Architects and operators who build and manage data analytics pipelines

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

As an AWS Advanced Training Partner, Cloud Wizard Consulting delivers this course with instructors who hold every AWS certification. With over 5,000 professionals trained, our team brings real-world implementation experience into the classroom, ensuring you leave with actionable skills - not just theoretical knowledge.