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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 pipeli
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2025/12/19
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