Stop reading dry documentation and start seeing AWS Analytics services in action!

The AWS Analytics ecosystem is incredibly powerful, but learning it from theory alone is difficult. To truly understand how to build a data pipeline, you need to see these services working together.

This course is built on one simple principle: learn by watching practical, hands-on demos.

We skip the long, boring theory slides and get straight into the AWS console. This course is a comprehensive collection of over-the-shoulder lab demonstrations where I walk you through the setup, configuration, and real-world use of the most important AWS Analytics services. You will see how to build, why we're clicking each button, and what the end result looks like.

This is not a "what is" course; this is a "how-to" course.

Join me as we build, configure, and run end-to-end analytics solutions. You will get detailed, practical demos of:

• Amazon Athena: Running serverless SQL queries directly on your S3 data.

• AWS Glue: Using crawlers to build a Data Catalog and running serverless ETL (Extract, Transform, Load) jobs.

• Amazon EMR: Launching and managing a big data cluster (like Spark) to process massive datasets.

• Amazon Redshift: Setting up a high-performance data warehouse and running complex analytical queries.

• Amazon QuickSight: Building and sharing interactive Business Intelligence (BI) dashboards to visualize your data.

• Amazon OpenSearch Service: Deploying a cluster for powerful log analytics, monitoring, and real-time search.

• Amazon MSK (Managed Kafka) & Kinesis: Understanding and configuring services for real-time data streaming.

• AWS Lake Formation: Building, securing, and managing a data lake in a matter of minutes.

• ...and more!

Amazon Athena: Running serverless SQL queries directly on your S3 data.

AWS Glue: Using crawlers to build a Data Catalog and running serverless ETL (Extract, Transform, Load) jobs.

Amazon EMR: Launching and managing a big data cluster (like Spark) to process massive datasets.

Amazon Redshift: Setting up a high-performance data warehouse and running complex analytical queries.

Amazon QuickSight: Building and sharing interactive Business Intelligence (BI) dashboards to visualize your data.

Amazon OpenSearch Service: Deploying a cluster for powerful log analytics, monitoring, and real-time search.

Amazon MSK (Managed Kafka) & Kinesis: Understanding and configuring services for real-time data streaming.

AWS Lake Formation: Building, securing, and managing a data lake in a matter of minutes.

...and more!

Who is this course for?

• Data Engineers and Data Analysts who want to learn to build pipelines on AWS.

• Solutions Architects who need to design modern data analytics solutions.

• Developers who need to integrate data streaming or analytics into their applications.

• Individuals preparing for the AWS Certified Data Analytics - Specialty exam.

• Any tech professional who learns best by "seeing" and "doing" rather than just reading slides.

Data Engineers and Data Analysts who want to learn to build pipelines on AWS.

Solutions Architects who need to design modern data analytics solutions.

Developers who need to integrate data streaming or analytics into their applications.

Individuals preparing for the AWS Certified Data Analytics - Specialty exam.

Any tech professional who learns best by "seeing" and "doing" rather than just reading slides.

If you're ready to gain practical, hands-on confidence in the AWS Analytics stack, this course is for you.

Enroll today and let's start building!