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