Synthetic Data for Logistics
Logistics data lives and dies by coherent time and geography. Misata orders tracking events correctly, computes route distances from real city coordinates using haversine plus road circuity, and derives travel times that make sense. Shipments reference real routes and carriers, and the whole dataset reproduces from a seed.
The tables Misata generates
shipmentsOrigin and destination, status lifecycle, ordered event timestampsroutesReal city pairs with haversine distance and derived travel timetracking_eventsDispatch, in transit, delivered, ordered per shipmentcarriersFleet references with shipment counts that roll upWhat holds true, every time
- Tracking events are chronologically ordered on every shipment
- Route distances come from real coordinates, not random numbers
- Every shipment references a real route and carrier
- Delivery timestamps stay consistent with dispatch and transit times
Frequently asked
Do I need real logistics data to generate this?
No. Misata builds the dataset from a specification, not a sample. There is no real logistics data to source, anonymize, or leak. You describe the tables you need and the engine constructs them with referential integrity and realistic distributions.
Is the generated logistics data privacy safe?
Yes, by construction. Nothing is learned from real records, so there is no membership to infer and nothing to leak. It runs entirely on your machine with no API key for the core engine.
Can I control the outcomes, like rates and totals?
Yes. Declare a target such as a monthly volume curve or an event rate and Misata produces rows that hit it exactly, while foreign keys stay intact and roll-up columns reconcile after a JOIN.
Choosing a tool? How Misata compares