Why should you care?

Banking dashboards need sums and averages across millions of transactions efficiently.

See it live — copy this example

Paste into your MeanVerse project (Angular + Express + MongoDB), then run with ng serve / node / mongosh as noted.

const pipeline = [
  { $match: { tenantId: 't_acme', createdAt: { $gte: startOfMonth } } },
  { $group: { _id: '$category', totalCents: { $sum: '$amountCents' }, count: { $sum: 1 } } },
  { $sort: { totalCents: -1 } },
  { $project: { category: '$_id', totalCents: 1, count: 1, _id: 0 } }
];
const summary = await Transaction.aggregate(pipeline);

What happened?

• $match filters like find.
• $group aggregates per category.
• $project renames _id to category for clean API JSON.

Practice next

1. Run pipeline in mongosh on sample transactions.
2. Add $lookup to join account name.
3. Index fields used in early $match stages.
4. Add $facet for paginated and total rows together.
5. Bucket transactions by week with $dateTrunc.

Remember

Pipeline = server-side data processing. Push $match early to reduce documents. Ideal for MeanVerse analytics endpoints.

CFO spend dashboard

MeanVerse SaaS shows MRR by plan tier from invoices collection.

Outcome: Aggregation returns chart-ready JSON in one DB round trip.