Fundamentals of Analytics on AWS – Part 2

Discover modern data architectures and cloud analytics solutions on AWS

Navigating modern analytics requires mastering data lakes, data warehousing, and key architectural principles. Examining AWS Lake Formation reveals how to overcome storage challenges, enforce governance, and transition from legacy warehouses.

Explore modern data architectures and data mesh strategies

Analysing data movement, reference architectures, and data mesh patterns helps identify optimal AWS services for complex workloads. Real-world use cases and knowledge checks confirm essential skills for building unified environments.

You’ll access learning content and practical activities online through Amazon Web Services (AWS), alongside your FutureLearn course experience, giving you direct access to AWS learning as you progress.

This course is ideal for cloud architects, data engineers, data analysts, data scientists, and developers

This course is ideal for cloud architects, data engineers, data analysts, data scientists, and developers

• Explain data lakes, benefits, and functions.
• Describe the basic data lake architecture, the AWS services used to build a data lake, and challenges with building a data lake.
• Explain AWS Lake Formation architecture, features and benefits.
• Explain data warehousing, challenges with an on-premises data warehouse, and available AWS solutions.
• Explain modern data architecture pillars and modern data architecture concepts.
• Explain data movement scenarios.
• Describe the data mesh architecture pattern, benefits, and available AWS solutions.
• Identify the available AWS services for building modern data architectures.
• Identify the components of modern data architecture.
• Describe common use cases for modern data architecture.