Warehouse Fulfillment and Billing Dataset
Compare order accuracy, handling effort and customer storage billing.
A practical workbook exercise for warehouse managers and account 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 480 source records across three related tables. The records are fictional and designed for descriptive business analysis.
Dataset details
| Industry | Warehousing and fulfillment |
| Formats | Excel workbook and CSV files |
| Source records | 480 |
| 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
- Clients: 20 records and 4 fields. One warehouse client.
- Orders: 400 records and 6 fields. One fulfillment order.
- Billing: 60 records and 6 fields. One client-month billing schedule.
Recommended analysis
- Which clients have the highest order shortfall?
- Which orders require the most handling time per unit?
- What storage and handling bill is implied by each client-month schedule?
- Which months have missing activity rather than zero shipments?
How to work with the data
Use the following relationships to connect the source tables:
- Orders.client_id → Clients.client_id
- Billing.client_id → Clients.client_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
- Storage rate is monthly, not daily. Handling rate applies per shipped unit.
- Use dispatch_date to match orders to billing_month. The source is the complete order population for these clients in the three months.
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.