Commercial Property Rent Collections Dataset
Reconcile monthly contractual rent with tenant receipts and late payments.
A practical workbook exercise for property accountants and asset 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 252 source records across three related tables. The records are fictional and designed for descriptive business analysis.
Dataset details
| Industry | Real estate and property management |
| Formats | Excel workbook and CSV files |
| Source records | 252 |
| 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
- Properties: 12 records and 4 fields. One property.
- Leases: 60 records and 5 fields. One lease active throughout the study period.
- Receipts: 180 records and 5 fields. One rent-month payment record. Zero amount records an unpaid month.
Recommended analysis
- Which tenants have unpaid rent by September 30?
- Which properties show the largest arrears?
- What changes when October cash is excluded?
- Can rent collection be used to infer occupancy?
How to work with the data
Use the following relationships to connect the source tables:
- Leases.property_id → Properties.property_id
- Receipts.lease_id → Leases.lease_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
- One contractual rent charge per active lease-month. Zero-payment records are explicit placeholders, not bank movements.
- A lease population alone does not establish occupied units or market vacancy.
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.