Problem
Order, product, and customer data lived in separate raw exports with inconsistent formats (mixed dates/casing, duplicate orders, typos, inconsistent statuses). Leadership couldn’t get a clean, consistent view of revenue, orders, AOV, returns, and product performance.

Solution
A repeatable Excel pipeline that uses Power Query to profile, clean, and standardize the raw eCommerce data into a single analysis-ready table. The workbook separates concerns across Raw Data → Data Dictionary → Cleaned Data → Analysis → Dashboard, so updates are simple and auditable.

What this model delivers

• Executive KPI block: Total Revenue, Total Orders, AOV, Return Rate, Net Result.
• Monthly trend: Revenue, Orders, AOV by month for the full 2024 period.
• Customer view: Unique customers and orders-per-customer.
• Product performance: Top products by revenue and quantity.
• Quality controls: De-dupes, standardized dates/casing, consistent order status.
• Ready for BI: Clean, modeled table that can be pushed to Power BI/SQL if needed.

How to use / update

1. Paste new exports into Raw Data in the same column structure.
2. Open Data → Refresh All to run Power Query steps.
3. Review Analysis and Dashboard tabs for updated KPIs and visuals.

Tools & techniques
Power Query (ETL), Pivot-driven KPIs, SUMIFS/COUNTIFS/Average formulas, dashboard layout/formatting.

Impact
Cuts manual prep from hours to minutes, standardizes reporting, and gives leaders a reliable, single source of truth for eCommerce performance.