This week I worked on something exciting: reporting routes for our backend that allow administrators to see key data at a glance and make informed decisions.
My goal was to create endpoints that transform raw student and payment data into useful information, including a list of all students, the number of students per track, total revenue, and revenue per track.
In practice, I was no longer just retrieving data; I was shaping it so an administrator could interpret it quickly and take action. On paper it seems simple, but the twist was that I had to use MongoDB's .aggregate() for the first time to group, filter, reshape fields, and perform calculations in a single operation.
Until then, my comfort zone was find and findOne. For these routes I needed more power, and .aggregate() turned out to be perfect. I learned to use the main stages of an aggregation such as $match to filter, $group to group, $sum to count or add, and $project to reshape the output.
A concrete case was counting students per track only if they were paid. With $match I filtered by paid status, with $group I grouped by track, and with $sum I obtained the count or the sum of revenue per track. With $project I cleaned up the output and renamed fields like _id to track so the result was clear and friendly for consumption by dashboards or APIs.
Seeing the data filtered, grouped, and presented exactly as we needed it was very satisfying. I discovered that MongoDB includes data analysis tools that make it easier to build reporting services integrated into custom applications and custom software.
At Q2BSTUDIO we apply this type of solution in custom application and custom software projects, combining business intelligence services and tools like Power BI for interactive dashboards. We also integrate artificial intelligence solutions and AI for businesses, AI agents, and pipelines that process data in AWS and Azure cloud services to ensure scalability and security.
In addition to accelerating operational decisions, these reporting routes add value to projects that require cybersecurity and compliance, because they centralize revenue and user activity metrics and facilitate audits and forensic analysis when necessary.
This experience was not just about adding new routes; it was about learning a new way of thinking about queries. At Q2BSTUDIO we are ready to bring these practices to your custom application and custom software projects, with integrated business intelligence, artificial intelligence, and cybersecurity services, and deployments on AWS and Azure cloud services with Power BI dashboards and AI agents when the case requires it.
If you are looking to turn data into decisions, our capabilities in artificial intelligence, AI for businesses, AI agents, Power BI, and AWS and Azure cloud services can help you obtain actionable insights and build robust and secure products.
