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Analyzed 2 years of e-commerce order data using SQL, writing queries with window functions to uncover sales trends over time. This query aggregates monthly sales and calculates a running total using SUM() OVER (ORDER BY), showing cumulative revenue growth from $189K in Jan 2023 to $4.04M by Dec 2024. Part of a broader set of 12+ analytical queries covering top products, category performance, regional breakdowns, and order-level profitability — built to answer real business questions directly from raw transactional data.
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:This is a self created portfolio demonstrating my Excel data management and analysis skills. I can work with various Excel features including data entry, data formatting, data validation,formulas, sum if/sum ifs conditional formatting, consolidation and reporting. This samples demonstrates my ability to turn raw data into clean, organised, and useful information.
I built this to show what a margin analysis actually produces.
"Sales are up and profit isn't" is the most common version of the question,
and the answer is usually counterintuitive — so it's a better demonstration
than something where the finding is obvious. On this order book the leak
turned out to be at the top, not the bottom: orders over £2,500 are 75% of
revenue at the worst margin on the book, while orders under £250 beat the
book average.
The order book is generated and the generator is published with it, so
every figure reproduces from scratch. That's deliberate. An analysis of a
real company's numbers can't be checked by anyone reading it.
I build custom Power BI dashboards that turn raw numbers into clear, actionable insights. From organizing backend data models with SQL and Power Query to writing custom DAX and designing clean reports, I help businesses make sense of their data without the headache.
