Freight Shipment Contribution Dataset
Join shipment costs and customer billing without multiplying invoice amounts by cost lines.
A practical workbook exercise for branch finance and logistics 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 900 source records across three related tables. The records are fictional and designed for descriptive business analysis.
Dataset details
| Industry | Freight forwarding and logistics |
| Formats | Excel workbook and CSV files |
| Source records | 900 |
| Related tables | 3 |
| Fields across table schemas | 13 |
| Reporting cutoff | September 30, 2026 |
| Currency | USD for monetary fields |
| Source | Original synthetic data created for Jolene.pro Workbook Studies |
What's included
- Shipments: 180 records and 5 fields. One shipment. Customer ID is a grouping label; customer names are not supplied.
- Charges: 540 records and 4 fields. One vendor cost component.
- Invoices: 180 records and 4 fields. One customer invoice per shipment.
Recommended analysis
- Which routes have the lowest shipment contribution?
- Which shipments have costs above billing?
- How much does accessorial spending contribute?
- What error appears if invoice totals are repeated per charge line?
How to work with the data
Use the following relationships to connect the source tables:
- Charges.shipment_id → Shipments.shipment_id
- Invoices.shipment_id → Shipments.shipment_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
- Aggregate charges to shipment before joining invoice amounts.
- Contribution excludes overhead and describes invoice amount minus listed direct charges. All billing dates are by September 30.
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.
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