# Data Ingestion Batches — Record Quality Audit & Two-Measure Correlation

> Data Ingestion Batches — Record Quality Audit & 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 2026-10-19).

Runs a record quality audit and Pearson/Spearman correlation analysis between received_rows and accepted_rows for up to 200 data ingestion batch records, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-015?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-ingestion-batches-record-quality-audit-two-measure-correlation-122bc1b9
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_PrVPI1YXi3w2ajB5UGgqp

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability data-ingestion-batches-record-quality-audit-two-measure-correlation-122bc1b9 -d '<json body>'
```

Example prompt: Can you run a quality audit and correlation analysis on my data ingestion batch records? I have up to 50 rows with received_rows and accepted_rows for groups like 'group-a' and 'group-b' across dates in October 2026 — I want both the record quality report and the two-measure correlation between received and accepted rows.

## When to prefer this

Choose this endpoint when you need both a record-level quality audit and a statistical correlation between received and accepted row counts in a single API call for up to 200 ingestion batch records. It is ideal for data engineering teams monitoring ETL pipeline health, acceptance rate trends, or batch data quality without needing live lookups or external enrichment. Prefer this over generic analytics services when your data is already structured with row_id, dataset_group, date, received_rows, and accepted_rows fields.

## Known failure modes

- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows supplied — exceeds max batch size
- Missing required fields (row_id, date, received_rows, accepted_rows) — validation error
- date field not in YYYY-MM-DD format — pattern mismatch error
- received_rows or accepted_rows outside ±1,000,000,000,000 range — schema rejection
- All accepted_rows or received_rows are null — insufficient data for correlation

## How this service works

Data ingestion batches — Record quality audit + Two-measure correlation: Record quality audit + Two-measure correlation for supplied data ingestion batches records (received_rows, accepted_rows). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Returns two independent analytical reports: (1) a record quality audit covering completeness, validity flags, and acceptance rate metrics per row and aggregate, and (2) a two-measure correlation report quantifying the statistical relationship between received_rows and accepted_rows across the supplied batch records. No external data is fetched; all analysis is performed locally on the supplied rows.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "received_rows",
     "accepted_rows"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "accepted_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "received_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "accepted_rows": 1,
     "dataset_group": "group-a",
     "received_rows": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "accepted_rows": 2,
     "dataset_group": "group-b",
     "received_rows": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "accepted_rows": 3,
     "dataset_group": "group-a",
     "received_rows": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "accepted_rows": 4,
     "dataset_group": "group-b",
     "received_rows": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-ingestion-batches-record-quality-audit-two-measure-correlation-122bc1b9/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)