Foundations of Data Intensive Applications
Large Scale Data Analytics under the Hood
Created by Supun Kamburugamuve, Saliya Ekanayake
Explore the inner workings of data-intensive applications and learn how large-scale analytics systems are designed and operated. You'll dive into distributed computing, storage choices, data formats, and the tradeoffs that shape performance and scalability.
Wiley | Sep 2026 | 416 min
What You Will Learn
You'll start by breaking down the core components of data-intensive applications, then connect those pieces to real-world analytics challenges. Each section builds your ability to reason about architecture, storage, and distributed execution, focusing on practical tradeoffs and system design.
Key Features
- Understand how distributed systems manage data, resources, and fault tolerance
- Evaluate storage options and data formats like JSON, Parquet, and Avro for analytics
- Analyze partitioning, replication, and memory models to optimize large-scale workloads
Target Audience
This course is designed for software engineers, data engineers, architects, analytics developers, and advanced students who want a deeper understanding of the systems behind large-scale analytics. If you're looking to design, build, or evaluate data-intensive applications, you'll gain the skills to make informed decisions about performance, storage, and scalability.
