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Transformation Throughput Analytics: Record Quality Audit + String Normalisation + Exact Row Deduplication
x402
Transformation Throughput Analytics: Record Quality Audit + String Normalisation + Exact Row Deduplication 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).
Audits record quality, normalises strings, and deduplicates rows in transformation throughput data (processed_rows, duration_seconds) for up to 200 supplied rows, returning 3 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Transformation throughput — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication 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
Three independent analytical reports: (1) a record quality audit flagging missing, null, or out-of-range values in the supplied rows; (2) a string normalisation report identifying and correcting inconsistencies in text fields such as dataset_group; and (3) an exact row deduplication report listing and removing fully duplicate rows. All analysis is performed locally on the supplied data with no external lookups.
Example use cases
ETL pipeline data quality check
“Can you run a quality audit, string normalisation, and deduplication on these 50 transformation throughput records from our nightly ETL jobs? They have row IDs, dataset groups, dates, processed_row counts, and duration in seconds — I want to find any bad data or duplicates before we load to the warehouse.”
Deduplicating pipeline performance logs
“I've got 120 rows of transformation throughput data — row IDs, groups, dates, processed_rows, and duration_seconds — and I suspect there are exact duplicate entries from a logging glitch. Can you run the deduplication and quality audit reports to identify them?”
Normalising dataset group strings in throughput metrics
“My team exported transformation throughput records across several dataset groups and I'm worried some group names have inconsistent capitalisation or spacing. Please run the string normalisation and quality audit on these 80 rows so I can see what needs cleaning before analysis.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-13-191?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three distinct data hygiene operations — quality audit, string normalisation, and exact deduplication — applied together to transformation throughput records (processed_rows and duration_seconds) in a single API call. It is ideal for pre-load data cleaning of ETL metrics, pipeline performance logs, or batch processing summaries with up to 200 rows. Prefer this over general-purpose analytics endpoints when your data specifically contains transformation throughput fields and you want all three reports bundled for $0.01 USDC.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, processed_rows, duration_seconds) causes row rejection
- Invalid date format (not YYYY-MM-DD) triggers a pattern validation error
- Submitting zero rows returns a minItems validation error
- Extremely large numeric values near the ±1,000,000,000,000 boundary may be flagged as anomalies
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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