Pharmaceutical Lot Inventory Dataset
Reconcile lot receipts and dispatches, then identify recorded expiry exposure.
A practical workbook exercise for inventory planners and distribution finance. Work from the underlying records, compare the relevant totals and explain how you reached your result.
About the dataset
This original synthetic dataset contains 315 source records across three related tables. The records are fictional and designed for descriptive business analysis.
Dataset details
| Industry | Pharmaceutical distribution |
| Formats | Excel workbook and CSV files |
| Source records | 315 |
| Related tables | 3 |
| Fields across table schemas | 15 |
| Reporting cutoff | September 30, 2026 |
| Currency | USD for monetary fields |
| Source | Original synthetic data created for Jolene.pro Workbook Studies |
What's included
- Products: 15 records and 4 fields. One fictional distribution product.
- Lots: 150 records and 6 fields. One received product lot.
- Dispatches: 150 records and 5 fields. One lot-level dispatch.
Recommended analysis
- Which lots have the highest remaining value?
- Which remaining lots expire in the next 60 days?
- How does expiry exposure differ by product?
- Can dispatch quantities be reconciled to received stock?
How to work with the data
Use the following relationships to connect the source tables:
- Lots.product_id → Products.product_id
- Dispatches.lot_id → Lots.lot_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
- Use the product’s stated unit. Do not aggregate unlike units as physical volume.
- Cutoff is September 30. Expiry is a recorded source date; this dataset does not determine clinical suitability or release products.
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.