Teams reach for realistic, shareable data for very different reasons. Here's who uses PrimaForja Supply, and what it unlocks for each of them.
Design executive and operational dashboards against a complete, cross-functional dataset — including C-level views most sample data can't support — and demo them to prospects without ever touching a customer's confidential numbers.
Develop and stress-test ETL/ELT jobs, dimensional models, and dbt projects against hundreds of millions of rows. Find the problems that only appear at volume — before production does.
Forecasting, churn, price-elasticity, anomaly-detection, and margin-optimization models all need patterned, temporally consistent data with real relationships. This dataset has them baked in.
Evaluate query performance, indexing, partitioning, and warehouse configuration under genuine scale and join complexity — not a toy schema.
Hand evaluators a rich, believable environment to try your product in, with zero risk of exposing anyone's confidential data and no data-sharing agreements to sign.
Give analysts, students, and course authors a safe, shareable dataset that mirrors the messiness of a real business — segments, seasonality, returns, and all.
"We're a BI vendor. Every demo used to start with an apology about the fake-looking sample data. Now we load PrimaForja Supply, and prospects see a CEO dashboard with a real EBITDA bridge, a CFO working-capital view, and pocket-margin analysis down to the customer — all reconciling to the same numbers. The conversation changes completely."
Because the data is coherent from the general ledger down to the individual shipment, a question asked in one dashboard can be answered — and cross-checked — in another. That's what turns a demo into a conversation about outcomes.
Production data carries privacy obligations, security exposure, and contractual limits, and it's rarely available to the vendors, prospects, and learners who need it. Synthetic data has none of that friction.
A few thousand rows in one table can't exercise a warehouse, train a model, or fill a C-suite dashboard. Scale, breadth, and cross-table integrity are the whole point.
Tell us what you're building and we'll help you get set up with the right edition of the dataset — full scale, a reduced footprint, or a custom configuration.
