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Transformation Throughput Analytics: Quality Audit + Deduplication + IQR Outlier Flags
x402
Transformation Throughput Analytics: Quality Audit + Deduplication + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-28).
Runs three independent analytical reports on transformation throughput records — record quality audit, exact row deduplication, and IQR-based outlier flagging — for up to 200 rows of processed_rows/duration_seconds data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Transformation throughput — Record quality audit + Exact row deduplication + IQR outlier flags: Record quality audit + Exact row deduplication + IQR outlier flags for supplied transformation throughput records (processed_rows, duration_seconds). 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 reports: (1) a record quality audit indicating completeness, validity, and consistency issues per row; (2) an exact row deduplication report identifying duplicate records; (3) IQR-based outlier flags marking statistically anomalous values in the selected numeric field (processed_rows or duration_seconds). All computed locally with no external lookups.
Example use cases
ETL pipeline data quality audit
“I've got about 80 rows of daily ETL job stats with columns for row_id, dataset_group, date, processed_rows, and duration_seconds. Can you run the quality audit, deduplication check, and IQR outlier detection on processed_rows so I can see if anything looks off before I trust this data?”
Detecting duplicate throughput records
“My data pipeline logs might have duplicate entries — can you check these 120 transformation throughput records for exact row duplicates, and also flag any quality issues and outliers in the duration_seconds field?”
Outlier flagging for processing duration monitoring
“I want to know if any of my batch processing runs have suspiciously high or low duration_seconds values. Here are 60 rows of throughput records with row_id, dataset_group, date, processed_rows, and duration_seconds — please run the IQR outlier flags, quality audit, and deduplication report on duration_seconds.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-13-220?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need simultaneous quality audit, exact deduplication, and IQR outlier detection on transformation throughput data (processed_rows, duration_seconds) in a single low-cost call. Ideal for data engineers validating ETL pipeline metrics before downstream use, especially when working with up to 200 rows and wanting three analytical perspectives at once without external lookups or live data connections.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, dataset_group, processed_rows, duration_seconds) cause validation failure
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Numeric values outside allowed range cause validation error
- Empty rows array returns error
- Invalid field enum value (not 'processed_rows' or 'duration_seconds') causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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