I built a comprehensive sales tracking spreadsheet for an engine oil business that automatically tracks daily sales, calculates profit per transaction and labels each sales. The client can instantly see their most profitable product, total revenue, total costs and net profit for any period without any manual calculations.

This is exactly the kind of clarity every small business owner needs — being able to see profit per transaction and top products at a glance without manual calculations is a game changer. Great work on the performance labelling too! 🙌

Designed and built a full data pipeline — pulling from multiple sources, resolving inconsistencies, enriching with external variables, and delivering clean outputs through interactive Power BI dashboards stakeholders can actually act on. Designed and built a full data pipeline — pulling from multiple sources, resolving inconsistencies, enriching with external variables, and delivering clean outputs through interactive Power BI dashboards stakeholders can actually act on.

The starting point was a large, structurally complex dataset with inconsistent formats, missing values, and misaligned fields. The goal was a repeatable pipeline that transformed it into something reliable enough to drive real decisions.

The enrichment layer was the differentiator: layering in demographic and contextual variables from external sources to add depth that the raw data alone couldn't provide. The final output was a Power BI dashboard built for non-technical audiences — clear enough to act on, rigorous enough to hold up to scrutiny.

AI-assisted validation (Claude Enterprise) was used throughout to cross-check outputs and flag inconsistencies before delivery