Mini Project: E-Commerce Analytics Dashboard

Welcome to the Week 3 Finale! 🏆

We’ve mastered $match, $group, $project, and $lookup. Now, we build a Real-Time Analytics Dashboard backend.

1. The Dataset

We have an Orders collection.

{
  "_id": 1,
  "date": ISODate("2025-08-16T10:00:00Z"),
  "status": "completed",
  "items": [
    { "product": "Laptop", "price": 1000, "qty": 1, "category": "Electronics" },
    { "product": "Mouse", "price": 50, "qty": 2, "category": "Electronics" }
  ],
  "userId": 101
}

2. Requirement: The “Boss” Dashboard 👔

The CEO wants an API that returns:

1. Total Items Sold (All time).
2. Top 3 Categories by Revenue.
3. Average Order Value (AOV) per Day.

3. The Mega Pipeline

We can do this in ONE database call using $facet (Multi-pipeline).

db.orders.aggregate([
  // 1. Filter out cancelled orders first
  { $match: { status: "completed" } },

  // 2. Facet: Fork the pipeline into 3 parallel processes
  {
    $facet: {
      "totalItems": [
        { $unwind: "$items" },
        { $group: { _id: null, count: { $sum: "$items.qty" } } }
      ],
      "topCategories": [
        { $unwind: "$items" },
        {
          $group: {
            _id: "$items.category",
            revenue: { $sum: { $multiply: ["$items.price", "$items.qty"] } }
          }
        },
        { $sort: { revenue: -1 } },
        { $limit: 3 }
      ],
      "dailyAOV": [
        {
          $group: {
            _id: { $dateToString: { format: "%Y-%m-%d", date: "$date" } },
            dailyRevenue: { $sum: { $sum: { $map: { input: "$items", as: "i", in: { $multiply: ["$$i.price", "$$i.qty"] } } } } },
            orderCount: { $sum: 1 }
          }
        },
        {
          $project: {
            date: "$_id",
            avgOrderValue: { $divide: ["$dailyRevenue", "$orderCount"] }
          }
        },
        { $sort: { date: -1 } }
      ]
    }
  }
])

4. The Result

{
  "totalItems": [ { "count": 5420 } ],
  "topCategories": [
    { "_id": "Electronics", "revenue": 50000 },
    { "_id": "Books", "revenue": 12000 },
    { "_id": "Home", "revenue": 8000 }
  ],
  "dailyAOV": [
    { "date": "2025-08-16", "avgOrderValue": 150.50 }
  ]
}

5. Week 3 Wrap Up

You have graduated from “basic queries”. You are now an Aggregation Pro. 🎓 You can filter, group, join, and reshape data without writing a single loop in Node.js.

Next Week: Week 4 - Transactions & Advanced Ops! 💳 We will handle money, atomic updates, and time-to-live data!

Enjoy your weekend! 🍹

Next Step

Next: Acid Transactions →