I Simulated A 1M+ High-Fidelity Retail POS Transaction Dataset Using Prolog And SQLCipher. Here Is Why It’s Structurally Sound.

The result is High-Fidelity Retail POS Transaction – 1M+ Dataset.

Key Technical Specifications:

• Volume: Over 1 million fully synchronized relational records.
• Security & Format: Encrypted using SQLCipher / SQLite database. All sensitive transaction IDs are pre-hashed via SHA-256 out of the box.
• Rich Features: Includes lifetime data log simulation, void logs (for fraud detection modeling), product health detection metrics, and multi-item checkouts.

Free Dowdload https://github.com/lokinpendawa/high-fidelity-pos-dataset-2M

WHAT YOU GET (FULL MULTI-FORMAT EXPORT):

• .sql (Transactional Database Dump – Postgres/MySQL ready)
• .json (NoSQL / API Mocking / Web development)
• .csv (Data Science / Pandas & Python ready)
• .pl (Prolog Fact Base for Logical Programming)