Wholesale Invoice Collections Dataset
Build a September collection list from issued invoices and directly linked payments.
A practical workbook exercise for credit controllers and finance 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 450 source records across three related tables. The records are fictional and designed for descriptive business analysis.
Dataset details
| Industry | Wholesale and distribution |
| Formats | Excel workbook and CSV files |
| Source records | 450 |
| Related tables | 3 |
| Fields across table schemas | 14 |
| Reporting cutoff | September 30, 2026 |
| Currency | USD for monetary fields |
| Source | Original synthetic data created for Jolene.pro Workbook Studies |
What's included
- Customers: 30 records and 4 fields. One trade customer.
- Invoices: 240 records and 6 fields. One issued invoice.
- Payments: 180 records and 4 fields. One directly assigned invoice payment.
Recommended analysis
- Which invoices are overdue at September 30?
- How much is still unpaid by customer and owner?
- Which payments must be excluded because they arrived after the reporting date?
- How does aging change after partial payments?
How to work with the data
Use the following relationships to connect the source tables:
- Invoices.customer_id → Customers.customer_id
- Payments.invoice_id → Invoices.invoice_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
- This simplified case has no credit notes, unallocated cash or opening invoices outside the table.
- Payments link directly to one invoice and never exceed its gross amount. Payment dates after September 30 are included for cutoff testing.
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.