{"uid":"cap_8w_RisKvintpr7nJjuPj_","slug":"data-pipeline-runs-two-measure-correlation-63195a86","name":"Data Pipeline Runs – Two-Measure Correlation","description":"Data pipeline runs - Two-measure correlation: Two-measure correlation for Data pipeline runs. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded two-measure correlation report.","url":"https://market.datapackvibe.com/x402/assistant-ar-analytics-pipeline-runs-correlation?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","pipeline","date","processed_rows","rejected_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"pipeline":{"type":"string","default":"","maxLength":80},"rejected_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"processed_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","pipeline":"group-a","rejected_rows":1,"processed_rows":10},{"date":"2026-10-02","row_id":"row-2","pipeline":"group-b","rejected_rows":2,"processed_rows":20},{"date":"2026-10-03","row_id":"row-3","pipeline":"group-a","rejected_rows":3,"processed_rows":15},{"date":"2026-10-04","row_id":"row-4","pipeline":"group-b","rejected_rows":4,"processed_rows":30}],"maxItems":200,"minItems":1}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_VUVXKdkxs9DZxUdUdRk3j","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Computes a two-measure (bivariate) correlation between processed_rows and rejected_rows across up to 200 data pipeline run records, returning a local descriptive analytics report.","exampleAgentPrompt":"Can you run a two-measure correlation analysis on these pipeline run records to see how strongly processed_rows and rejected_rows are related? I have records for pipelines group-a and group-b across October 2026.","exampleUseCases":[{"title":"ETL quality drift investigation","prompt":"I've got daily pipeline run logs for the past few months — can you correlate processed_rows and rejected_rows to tell me whether rejection rates tend to rise as throughput increases?"},{"title":"Pipeline health comparison across groups","prompt":"Here are 150 pipeline run records split across group-a and group-b pipelines — run a two-measure correlation on processed and rejected row counts so I can see if the relationship differs meaningfully."},{"title":"Data reliability reporting for stakeholders","prompt":"I need a statistical summary showing how correlated our data rejection volume is with overall pipeline throughput — can you compute the two-measure correlation from these run records so I can include it in the quarterly data quality report?"}],"resultDescription":"A bounded two-measure correlation report covering the relationship between processed_rows and rejected_rows across the submitted pipeline run records. Includes a correlation coefficient and supporting descriptive statistics. No forecasting or external data enrichment is performed — analysis is purely local to the supplied dataset.","failureModes":["Fewer than 1 row submitted (minItems:1 violation)","More than 200 rows submitted (maxItems:200 violation)","Missing required fields (row_id, pipeline, date, processed_rows, rejected_rows)","Invalid date format (must match YYYY-MM-DD pattern)","Numeric values outside allowed range (±1,000,000,000,000)","Insufficient variance in one measure prevents meaningful correlation calculation","Payment failure or insufficient USDC balance"],"whenToPreferThis":"Choose this endpoint when you have up to 200 structured pipeline run records and need a fast, local bivariate correlation between processed_rows and rejected_rows without any external enrichment or forecasting. Ideal for data engineers or analysts who want a quick statistical signal about the relationship between pipeline throughput and rejection rate as part of a lightweight analytics workflow or report.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T19:05:32.045Z","isFirstParty":false,"canonicalSlug":"data-pipeline-runs-two-measure-correlation-63195a86"}