The year as the numbers tell it. A yearly report that gives a clear view of revenue performance all year long.

Case study

1. Overview

   Actual Revenues 2024, an internal initiative I took on for the sales side of the business. I was the analyst end to end, from sourcing and cleaning to the model and the dashboard, working in Excel, Python, SQL and Power BI.

2. Problem

   Revenue lived in 12 separate Excel files. Pulling one clear number took over an hour of switching between them, and every new question from the sales team cost that hour again.

3. Research

   The work started from the review of the first dashboard, where the sales team said what they still could not see. The questions they kept coming back with were exactly the ones that took an hour to answer. I then went through all 12 files to find where they disagreed: different column names, categories spelled two ways, and quarters split by file instead of by field.

4. Process

   I merged the 12 sources into one cleaned dataset and pointed the dashboard at it, so the category view and the quarterly view are two readings of a single table rather than two separate reports. The obvious alternative was to keep merging the files by hand whenever someone asked. I dropped it because it repeats the same hour every month and leaves no version anyone else can check.

5. Result

   A yearly Power BI report breaking revenue down by category across all four quarters. The recording below moves from the yearly total to the quarterly split to revenue by category.

6. Impact

   Finding a number went from over an hour to under a minute, 12 files became one dataset, and all four quarters sit in one report the sales team opens themselves.

7. Takeaway

   The real deliverable was not the dashboard, it was making the underlying data reusable so the next question does not cost another hour. What I would change: agree the category names with the sales team before merging, instead of reconciling their spellings afterwards.