Pepperwind is a large synthetic dataset built around a fictional spice and tea trader based in Kochi, operating in India, Europe, and the United States. Across 223 tables, it contains 79 million rows, supplied as about 7 GB of Parquet files. Its systems cover retail, subscriptions, warehousing, multi-currency accounting, customer support, CRM, marketing analytics, HR, payroll, and company email. The project addresses a shortage of realistic test data for products that connect multiple business systems: records should refer consistently to the same customers and entities, foreign keys should work, and financial figures should reconcile. A browser preview lets users inspect part of the data and trace an individual customer across systems.
The dataset is designed to support testing and analysis, not merely provide realistic-looking records. The ledger balances, and 20 coordinated incidents are embedded across systems, including a Diwali courier failure, incorrectly charged Dutch VAT, referral fraud, and subscription churn following a price increase. It also includes monthly values for 92 KPIs and 420 questions users can ask of the data. Pepperwind was generated with Misata Studio’s backend; Misata is developing a from-scratch, multi-table synthetic-data generator, with an open-source Python library and a web tool for generating datasets from prompts. The full dataset is currently paid, while a preview is free; it is listed on Hugging Face under CC BY 4.0. Its creator is seeking feedback on potential applications and use cases.
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