The data you could never get, with the answer key inside
Real data never tells you why: why a claim was denied, which cause shifted a control chart, how long a machine really had left, what demand the empty shelf lost. Each of these datasets carries that truth in its own columns, so a model or a dashboard can be checked against it. Every table is profiled below, every check is listed, and every dataset has a free preview.
4 datasets · 3,820,562 rows · 337 audit checks passed · $15 each
- fact_store_item_day, rows per monthFeb 2024 – Jan 2026
Grocery chain, 10 stores, fiscal 2024 and 2025
Two fiscal years of a grocery chain, from the shelf to the receipt
- Rows
- 2,780,138
- Tables
- 14
- Checks
- 110 of 110
- readings, rows per monthJan 2025 – Jun 2025
3 plants, 36 CNC machines, six months
Six months of control charts with the ground truth underneath
- Rows
- 504,786
- Tables
- 15
- Checks
- 78 of 78
- readings, rows per monthJan 2024 – Dec 2025
240 machines at 4 plants, two years
Two years of sensor readings, failures, repairs and costs for 240 machines
- Rows
- 179,029
- Tables
- 6
- Checks
- 62 of 62
- claims, rows per monthJan 2025 – Dec 2025
10 payers, 8 facilities, calendar 2025
A year of revenue cycle with the reason behind every denial
- Rows
- 356,609
- Tables
- 8
- Checks
- 87 of 87