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Pipeline Durations Analytics: Record Quality Audit + String Normalisation + Two-Measure Correlation
x402
Pipeline Durations 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 2026-10-10).
Runs three bundled analytical reports on pipeline duration records — a data quality audit, string normalisation, and Pearson/Spearman correlation between run_seconds and processed_rows — for up to 200 rows at $0.01 USDC.
Price / call$0.01
Success—
StatusUnknown
How this service works
Pipeline durations — Record quality audit + String normalisation + Two-measure correlation: Record quality audit + String normalisation + Two-measure correlation for supplied pipeline durations records (run_seconds, processed_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
Three independent analytical reports returned in a single response: (1) a record quality audit flagging nulls, out-of-range values, and malformed fields; (2) a string normalisation report standardising dataset_group labels; (3) a two-measure correlation report (e.g. Pearson/Spearman) between run_seconds and processed_rows, all computed locally against the supplied rows with no external data fetched.
Example use cases
ETL pipeline health check
“I have a CSV export of our nightly ETL pipeline runs — about 120 rows with columns for run_id, dataset_group, date, run_seconds, and processed_rows. Can you audit the data quality, normalise the group name strings, and tell me if there's a correlation between how long the job ran and how many rows it processed?”
Throughput-duration correlation study
“We're trying to understand whether longer pipeline runs actually process more rows or if something's off. I've got 80 records with run_seconds and processed_rows — can you run a two-measure correlation analysis and flag any data quality issues at the same time?”
Dataset group label cleanup
“Our pipeline logs have messy dataset_group values — inconsistent casing and spacing across about 60 records. Can you normalise those strings, do a quality audit on the whole batch, and also check if there's any meaningful correlation between run time and processed row count?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-05-204?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical operations — quality audit, string normalisation, and bivariate correlation — on pipeline duration data in a single low-cost call. Prefer it over general analytics APIs when your data is pipeline execution logs with run_seconds and processed_rows fields, you want offline/local computation with no external lookups, and you need all three reports for $0.01 USDC rather than paying for separate services.
Side effects
- Fewer than 1 row submitted — rejected by minItems constraint
- More than 200 rows submitted — rejected by maxItems constraint
- Missing required fields (row_id, date, run_seconds, processed_rows, dataset_group) — validation error
- Date not matching YYYY-MM-DD pattern — schema validation failure
- run_seconds or processed_rows outside ±1e12 bounds — schema rejection
- Insufficient numeric variance in measures — correlation may be undefined or NaN
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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