Aggregation for reporting dashboards in MongoDB - Mini Project: Build & Apply

Aggregation for reporting dashboards

📖 Scenario: You work for an online store that wants to create a simple sales report dashboard. The dashboard will show total sales and the number of orders per product category.

🎯 Goal: Build a MongoDB aggregation pipeline step-by-step to calculate total sales and order counts grouped by product category.

📋 What You'll Learn

Create a sales collection with sample sales documents

Add a filter stage to select sales from the last month

Group sales by category to calculate total sales amount and order count

Sort the results by total sales in descending order

💡 Why This Matters

🌍 Real World

Aggregation pipelines are used in real dashboards to summarize and analyze sales data quickly.

💼 Career

Understanding aggregation is essential for data analysts and backend developers working with MongoDB to build reports.

1

DATA SETUP: Create the sales collection with sample documents

Create a variable called sales that contains an array of 5 sales documents. Each document must have these exact fields and values: { product: 'Laptop', category: 'Electronics', amount: 1200, date: new Date('2024-05-10') }, { product: 'Headphones', category: 'Electronics', amount: 150, date: new Date('2024-05-15') }, { product: 'Coffee Maker', category: 'Home Appliances', amount: 80, date: new Date('2024-05-20') }, { product: 'Blender', category: 'Home Appliances', amount: 60, date: new Date('2024-04-25') }, { product: 'Notebook', category: 'Stationery', amount: 5, date: new Date('2024-05-18') }.

MongoDB

# Create a variable called sales with 5 sales documents as described
# Your code here

Need a hint?

Use const sales = [ ... ] and include the exact documents with the given fields and values.

2

CONFIGURATION: Define the date filter for last month sales

Create a variable called lastMonth and set it to a JavaScript Date object representing May 1, 2024.

MongoDB

const sales = [
  { product: 'Laptop', category: 'Electronics', amount: 1200, date: new Date('2024-05-10') },
  { product: 'Headphones', category: 'Electronics', amount: 150, date: new Date('2024-05-15') },
  { product: 'Coffee Maker', category: 'Home Appliances', amount: 80, date: new Date('2024-05-20') },
  { product: 'Blender', category: 'Home Appliances', amount: 60, date: new Date('2024-04-25') },
  { product: 'Notebook', category: 'Stationery', amount: 5, date: new Date('2024-05-18') }
];

// Create a variable lastMonth set to new Date('2024-05-01')
# Your code here

Need a hint?

Use const lastMonth = new Date('2024-05-01') to set the date filter.

3

CORE LOGIC: Build the aggregation pipeline to filter and group sales

Create a variable called pipeline that is an array with these stages: 1) a $match stage to filter sales with date greater than or equal to lastMonth, 2) a $group stage that groups by category and calculates totalSales as the sum of amount and orderCount as the count of documents.

MongoDB

const sales = [
  { product: 'Laptop', category: 'Electronics', amount: 1200, date: new Date('2024-05-10') },
  { product: 'Headphones', category: 'Electronics', amount: 150, date: new Date('2024-05-15') },
  { product: 'Coffee Maker', category: 'Home Appliances', amount: 80, date: new Date('2024-05-20') },
  { product: 'Blender', category: 'Home Appliances', amount: 60, date: new Date('2024-04-25') },
  { product: 'Notebook', category: 'Stationery', amount: 5, date: new Date('2024-05-18') }
];

const lastMonth = new Date('2024-05-01');

// Create an aggregation pipeline array with $match and $group stages
# Your code here

Need a hint?

Use { $match: { date: { $gte: lastMonth } } } and { $group: { _id: "$category", totalSales: { $sum: "$amount" }, orderCount: { $sum: 1 } } } in the pipeline array.

4

COMPLETION: Add a $sort stage to order results by total sales

Add a $sort stage to the pipeline array that sorts documents by totalSales in descending order.

MongoDB

const sales = [
  { product: 'Laptop', category: 'Electronics', amount: 1200, date: new Date('2024-05-10') },
  { product: 'Headphones', category: 'Electronics', amount: 150, date: new Date('2024-05-15') },
  { product: 'Coffee Maker', category: 'Home Appliances', amount: 80, date: new Date('2024-05-20') },
  { product: 'Blender', category: 'Home Appliances', amount: 60, date: new Date('2024-04-25') },
  { product: 'Notebook', category: 'Stationery', amount: 5, date: new Date('2024-05-18') }
];

const lastMonth = new Date('2024-05-01');

const pipeline = [
  { $match: { date: { $gte: lastMonth } } },
  { $group: { _id: "$category", totalSales: { $sum: "$amount" }, orderCount: { $sum: 1 } } },
  // Add $sort stage here
];
# Your code here

Need a hint?

Add { $sort: { totalSales: -1 } } as the last stage in the pipeline array.