---
title: "Module Overview: Data-Intensive Systems"
weight: 0
summary: "Storage models, indexing, pipelines, and scaling for data-heavy workloads."
---

# Module Overview: Data-Intensive Systems

**"Design a system that stores and queries massive datasets."**

This module focuses on data modeling, storage choices, and architecture patterns for systems where data volume, query performance, and correctness dominate the design.

## Learning Goals

- Choose storage engines based on access patterns
- Apply indexing, partitioning, and caching strategies
- Model pipelines (ingest → process → serve) with clear responsibilities
- Reason about durability, retention, and cost

## Interview Preparation

- ✅ Explain OLTP vs OLAP trade-offs
- ✅ Discuss partition keys, hotspots, and compaction
- ✅ Design pipelines and serving layers

## Real-World Application

- Analytics and reporting platforms
- Search and recommendation backends
- Event data lakes and warehouses

## Estimated Time

45-60 minutes (includes practice)

## Checklist

- [ ] Can map queries to storage choices
- [ ] Can design partitions and indexes
- [ ] Can explain retention and backfills
