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Duplicate Observations Analytics: Record Quality Audit, String Normalisation & Two-Measure Correlation
x402
Duplicate Observations Analytics: Record Quality Audit, String Normalisation & Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).
Runs three local analytical reports on supplied duplicate-observation records: a record quality audit, string normalisation, and a two-measure correlation between duplicate_rows and total_rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Duplicate observations — Record quality audit + String normalisation + Two-measure correlation: Record quality audit + String normalisation + Two-measure correlation for supplied duplicate observations records (duplicate_rows, total_rows). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Returns three independent analytical reports for the submitted rows (up to 200): (1) a record quality audit flagging issues such as nulls, out-of-range values, or malformed dates; (2) a string normalisation report highlighting inconsistencies in text fields like dataset_group; and (3) a two-measure correlation report quantifying the relationship between duplicate_rows and total_rows across the supplied records. All analysis is performed locally with no external lookups or predictions.
Example use cases
ETL pipeline duplicate record audit
“I need to audit the quality of duplicate records coming out of our ETL pipeline. Here are 5 rows with date, dataset group, duplicate_rows, and total_rows — can you run a full quality audit, normalize the string fields, and correlate duplicate_rows against total_rows for me?”
Data warehouse duplicate rate analysis
“We have a data warehouse table and I want to understand how duplicate rows correlate with total row counts across our dataset groups over the last week. Can you run a two-measure correlation plus a record quality audit on these 10 daily observations?”
Dataset group string consistency check
“Our dataset group labels might have inconsistent casing or whitespace issues across these 15 duplicate observation records. Can you run a string normalisation report plus a record quality audit so I can see what needs cleaning before we load to production?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-04-204?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a bundled, cost-effective ($0.01 USDC for all three reports) offline analytical pass over a small batch of duplicate-observation records (up to 200 rows) and require record quality auditing, string field normalisation, and numeric correlation in a single call with no external data dependencies.
Side effects
- Fewer than 1 row submitted — minimum 1 row required
- More than 200 rows submitted — hard cap enforced
- Malformed date strings not matching YYYY-MM-DD pattern
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows)
- Numeric fields outside allowed range (-1e12 to 1e12)
- Payment failure or insufficient USDC balance
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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