MongoDB Coding Challenges: Business Problems

Calculate Top Selling Products

Write an aggregation pipeline to find the top 5 products by total sales amount in the last quarter.

Expected output: A list of top 5 product IDs with their total sales amounts.

Hint: Filter orders by date, unwind items array, group by product ID, sum sales, and sort descending.

Identify Low Stock Products

Query the inventory collection to find products with stock quantity below a threshold of 10.

Expected output: Documents of products with stock less than 10.

Hint: Use a simple find query with a filter on the stock field.

Segment Customers by Purchase Frequency

Create an aggregation pipeline that groups customers by the number of orders placed: 1-3, 4-6, and 7+.

Expected output: Buckets showing customer counts per purchase frequency range.

Hint: Group orders by customer ID, count orders, then bucket counts into ranges.

A sales order can be modeled as a document containing customer info, order date, an array of purchased items with quantities and prices, and status fields. Embedding items allows quick access, while referencing customers separately can avoid duplication.

The aggregation framework with operators like $group, $sum, and date extraction operators ($year, $month) enables grouping sales data by time periods such as months or years.

Create indexes on fields used in filters and sorts, use aggregation pipelines to reduce data transferred, and design schemas that minimize the need for expensive joins or lookups.