Ecommerce Orders and Settlements Dataset
Trace order gross, refunds and platform fees to settlement batches.
A practical workbook exercise for ecommerce finance and data analysts. Work from the underlying records, compare the relevant totals and explain how you reached your result.
About the dataset
This original synthetic dataset contains 650 source records across three related tables. The records are fictional and designed for descriptive business analysis.
Dataset details
| Industry | Ecommerce and marketplaces |
| Formats | Excel workbook and CSV files |
| Source records | 650 |
| Related tables | 3 |
| Fields across table schemas | 16 |
| Reporting cutoff | September 30, 2026 |
| Currency | USD for monetary fields |
| Source | Original synthetic data created for Jolene.pro Workbook Studies |
What's included
- Products: 20 records and 4 fields. One product; unit cost is per unit, not per order.
- Orders: 600 records and 8 fields. One single-product order, with all amounts stated at order level.
- Settlements: 30 records and 4 fields. One platform settlement batch.
Recommended analysis
- Does each settlement match its order-level deductions?
- Which batches were paid by September 30?
- Which channels have higher refund shares?
- Why does gross order value differ from bank cash?
How to work with the data
Use the following relationships to connect the source tables:
- Orders.product_id → Products.product_id
- Orders.settlement_id → Settlements.settlement_id
Check the row grain before joining. Aggregate repeated child records to the required level before combining totals, so parent amounts are not counted more than once.
You can explore the workbook in Excel or Jolene.pro, or use the CSV files with SQL, Power BI and other analysis tools.
Definitions and assumptions
- Orders omit unit quantities, so unit product costs cannot be used to infer full order profit.
- A Paid status is the final export status; use settlement_date to determine cash paid by September 30. Pending batches are not paid.
Use the field definitions and nullable-column guidance in the included data dictionary. Interpret blank values and reporting dates according to the scenario notes.
Downloads
The complete dataset ZIP includes the Excel workbook, three matching CSV files, a data dictionary, scenario notes, a source-row preview and license details.
Reuse and attribution
These are synthetic records, not customer data or industry benchmarks. Reuse is allowed under Creative Commons Attribution 4.0 International (CC BY 4.0). Credit Jolene.pro and identify any changes you make.