Real-World MongoDB Projects: Building an Analytics Dashboard

Build a Simple Sales Dashboard

Design a MongoDB schema and aggregation pipeline to display total sales per product category for the last quarter.

Expected output: An aggregation result showing total sales per category for the specified period.

Hint: Use $match to filter dates, $group by category, and $sum sales amounts.

Optimize Dashboard Queries

Analyze a given aggregation pipeline and suggest indexing strategies to improve performance.

Expected output: A list of recommended indexes and rationale.

Hint: Identify fields used in $match and $group stages for indexing.

MongoDB's aggregation framework allows processing and transforming data within the database using pipelines, enabling efficient computation of metrics like sums, averages, and counts essential for analytics dashboards.

Key considerations include choosing between embedding and referencing based on data size and update frequency, designing collections to support aggregation queries, and indexing fields used in filters and groupings.

Real-time updates can be achieved using MongoDB change streams to listen for data changes, combined with frontend technologies like WebSockets to push updates to the dashboard interface.