Category-level revenue answers, self-service instead of a request queue.

Case study

1. Overview

   Camp Operations Dashboard, an internal initiative built after the 2024 revenue report. I was the analyst: SQL against the source database, a cleaned data model, and one interactive Power BI dashboard covering revenue by category.

2. Problem

   The initial report answered how much revenue was generated, but not where it came from or how categories compared to each other. Every new question meant another manual request, another export, and another round of waiting, which slowed decision-making down.

3. Research

   Stakeholders came back with follow-up questions the original report did not cover. They wanted visibility at the category level: how each category performed individually, and what the average revenue per category was. Those questions set the scope of the screen.

4. Process

   I wrote SQL queries against the source database to export the specific category-level fields the existing system reports did not expose, then restructured and reorganised the extracted data into a clean model suitable for analysis. I tested several dashboard layouts before settling on the structure that surfaced the key comparisons fastest.

5. Result

   An interactive Power BI dashboard covering revenue by category, category averages, and comparative performance, built so stakeholders could filter and drill down themselves instead of requesting a new report each time.

6. Impact

   Answers to recurring business questions became self-service rather than a manual request cycle. That saved significant analyst time and reporting cost, and gave decision-makers faster access to category-level insight, supporting better-informed decisions.

7. Takeaway

   The first report answered the question that was asked. The dashboard answered the questions that came after, which turned out to be the more valuable deliverable.