In this video, we are continuing our deep dive into the MongoDB Aggregation Pipeline by mastering three essential tools for data shaping and analysis: $min, $max, and $addFields. These operators allow you to extract the "extremes" of your data and dynamically update your documents with new information without changing the underlying data in your collection. Whether you are building a dashboard to track record-breaking sales or simply trying to clean up your API responses, this tutorial covers everything you need to know.

We kick things off with the $min and $max accumulators. These are your go-to tools for finding the lowest and highest values within a dataset. We show you how to use them inside a $group stage to identify things like the cheapest product in a category, the most recent login for a user, or the peak temperature recorded by an IoT sensor. We also explain how MongoDB handles different data types—like dates, strings, and numbers—when calculating these extremes, so you can avoid common pitfalls when working with mixed data.

The second half of the video focuses on the $addFields stage, one of the most useful tools for backend developers. Unlike the $project stage, which requires you to list every single field you want to keep, $addFields allows you to simply append new calculated fields to your existing documents while keeping everything else intact. We walk through real-world examples, such as calculating a "total price" by adding tax to a base cost, or creating a "full name" field by combining first and last names.

We also discuss the performance benefits of using $addFields versus $project and show you how to chain these stages together to create clean, readable, and highly efficient pipelines. By the end of this video, you will have a solid grasp of how to analyze data boundaries and transform your documents on the fly to meet the specific needs of your application.

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Tags: MongoDB, Aggregation Pipeline, $min, $max, $addFields, MongoDB Tutorial, Data Analytics, NoSQL, Backend Development, Database Reporting, MongoDB Optimization, Query Building, Software Development, Data Transformation, Database Administration, MongoDB Aggregations