Ready to master the most powerful tool in MongoDB? In this video, we move beyond basic queries and build a complete E-commerce Analytics Project using the Aggregation Framework. We will transform raw "Order" and "Customer" data into a professional sales report—all within the database!

This is a hands-on project tutorial designed for developers who want to see how $match, $lookup, and $group work together in a production-style environment.

The Project Goal: Calculate the total spending per customer for all "Completed" orders, join their personal details, and identify our Top 5 High-Value Clients.

Stages We’ll Build in the Pipeline:

$match: Filter out cancelled or pending orders to focus only on successful sales.

$lookup: Perform a "Left Outer Join" to bring in customer names and emails from a separate users collection.

$unwind: Flatten the joined customer data so it's easy to work with.

$group: The heavy lifting! We'll group by customer ID and calculate their total spent using the $sum operator.

$addFields: Dynamically calculate a "Loyalty Status" (Gold/Silver) based on their total spending.

$sort & $limit: Order the results by the biggest spenders and grab the top 5 for our report.

What You Will Learn:

How the "Assembly Line" logic of a pipeline actually works.

How to handle relational data in a NoSQL environment using $lookup.

Tips for optimizing performance by placing stages in the correct order.

How to use MongoDB Compass to visualize your pipeline stages in real-time.

By the end of this video, you won't just know the commands—you'll understand how to architect complex data transformations that make your applications faster and your code cleaner.

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