Build modern, scalable data analytics solutions across the AWS data platform.
This comprehensive 4-day program combines four official AWS data analytics courses into one intensive learning experience. Participants gain hands-on experience across the modern data analytics stack, including scalable data lakes, cloud data warehousing with Amazon Redshift, batch processing with Amazon EMR, and real-time streaming analytics with Amazon Kinesis and Amazon MSK.
- Why get trained: Gain practical skills across data lakes, data warehousing, batch processing, and real-time streaming analytics on AWS.
- Why it matters: Build scalable and reliable data pipelines that support modern analytics, business intelligence, and data-driven decision-making.
- Who should attend: Data Platform Engineers, Solutions Architects, Data Warehouse Engineers, Data Engineers, Analytics Developers, and IT Professionals building data pipelines.
Participants gain practical experience with AWS data analytics technologies through an intensive, hands-on learning approach. HRD Corp Claimable.

Overview
Building Modern Data Analytics Solutions on AWS is a comprehensive 4-day program that combines four official AWS data analytics courses into one intensive training.
Participants will gain hands-on expertise across the full modern data analytics stack — from building scalable data lakes, to cloud data warehousing with Amazon Redshift, batch processing with Amazon EMR, and real-time streaming analytics with Amazon Kinesis and Amazon MSK.
Skills Covered
- Apply data lake methodologies in planning and designing a data lake
- Query, analyze, and visualize data within a data lake
- Design and implement a data warehouse analytics solution
- Select and deploy options to ingest, transform, and store data
- Design and implement a batch data analytics solution on AWS
- Identify and apply techniques including compression to optimize data storage
- Design and implement a streaming data analytics solution
- Apply techniques to optimize streaming data storage and processing
Prerequisites
- Completed AWS Technical Essentials (or Architecting on AWS)
- 1+ year of experience building data analytics pipelines
- Completed Data Analytics Fundamentals digital course (alternative to experience)
- For Days 2–4: Completion of prior day(s) recommended
Target Audience
- Data platform engineers
- Solutions architects
- Data warehouse engineers
- Data engineers and analytics developers
- IT professionals building data pipelines

Day 1: Building Data Lakes on AWS
Learn to build scalable and secure data lakes with AWS Lake Formation while optimizing for cost and performance. You will learn the components and functionality of the services involved in creating a data lake, use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data — covering both structured and unstructured data.
Day 2: Building Data Analytics Solutions Using Amazon Redshift
Build a data analytics solution using Amazon Redshift, a cloud data warehouse service. The course focuses on data collection, ingestion, cataloging, storage, and processing. You will learn to integrate Amazon Redshift with a data lake to support both analytics and machine learning workloads, and apply security, performance, and cost management best practices.
Day 3: Building Batch Data Analytics Solutions on AWS
Learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Hadoop managed service. The course covers how Amazon EMR integrates with Apache Hive, Hue, HBase, AWS Glue, and AWS Lake Formation. You will use EMR Notebooks for analytics and machine learning, and apply security, performance, and cost best practices.
Day 4: Building Streaming Data Analytics Solutions on AWS
Learn to build streaming data analytics solutions using Amazon Kinesis and Amazon MSK. Build stream producers and consumers, and use Amazon Kinesis Data Analytics with Apache Flink for real-time analytics. The course also covers Amazon MSK for streaming pipelines and applies security, monitoring, and cost optimization best practices throughout.
Dates & Locations
January 18, 2027 - January 21, 2027
January 18, 2027 - January 21, 2027
March 1, 2027 - March 4, 2027
March 1, 2027 - March 4, 2027
May 25, 2027 - May 28, 2027
May 25, 2027 - May 28, 2027
July 5, 2027 - July 8, 2027
July 5, 2027 - July 8, 2027
September 6, 2027 - September 9, 2027
September 6, 2027 - September 9, 2027
November 16, 2027 - November 19, 2027
November 16, 2027 - November 19, 2027

Exam & Certification
There is no exam directly associated with this course. However, AWS offers an extensive portfolio of industry-recognized certifications that can help you stand out as a tech professional in 2026 and beyond. Achieving AWS credentials is one of the most effective ways to validate your skills and accelerate your career.
With our expert-led training, you’ll be prepared to:
- Master in-demand capabilities across Cloud, Data & AI, and Cybersecurity — areas driving global digital transformation.
- Prove your expertise with a globally respected credential recognized by employers worldwide.
- Advance your career by enhancing your credibility, increasing your earning potential, and opening doors to new opportunities.
Explore our top AWS Certifications for 2026 and start building the skills that matter today.
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All courses are HRD Claimable.
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