Requirements Analysis and Schema Design
Learners will translate application requirements into a MongoDB schema, choosing embedding vs referencing and applying design patterns appropriately.
The Capstone: Designing a Real Application
In this capstone lesson, you apply all the knowledge from the MongoDB track to design a production-ready application from scratch. We will build a multi-vendor e-commerce platform — a domain rich enough to exercise embedding vs referencing decisions, index planning, aggregation design, and security. The process starts with requirements analysis, which drives every schema decision that follows.
Step 1: Gather Functional Requirements
Begin by listing the application's core entities and operations. For our e-commerce platform: entities — Users, Vendors, Products, Orders, Reviews, Carts; operations — browse products by category, search by keyword, place orders, process payments, track shipping, and write reviews. Each operation maps to one or more MongoDB queries, and those queries drive schema decisions.
// Requirement analysis output (pseudocode spec)
const requirements = {
reads: [
'Get product by slug (very high frequency)',
'List products by category + sort/filter (high frequency)',
'Search products by keyword (high frequency)',
'Get order history for a user (medium frequency)',
'Get order detail (medium frequency)'
],
writes: [
'Create order (medium frequency)',
'Update order status (medium frequency)',
'Add product review (low frequency)',
'Update product inventory (high frequency)'
]
}All lessons in this course
- Requirements Analysis and Schema Design
- Index Strategy and Query Planner Validation
- Scaling Plan: Replica Set to Sharded Cluster
- Security Hardening and Production Checklist