{"uid":"cap_k1YnnXj9ZImTkFHcPHLFP","slug":"data-ingestion-batches-string-normalisation-exact-row-deduplication-9835a5bc","name":"Data Ingestion Batches — String Normalisation + Exact Row Deduplication","description":"Data ingestion batches — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication 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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-020?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"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}}},"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_1KI7w928EJRyJ6Z_DNpSk","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":"Normalises strings and deduplicates exact rows in data ingestion batch records (received_rows, accepted_rows), producing 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you normalise the strings and find exact duplicate rows in my data ingestion batch? I have records with row IDs row-1 through row-4, dataset groups group-a and group-b, dates from 2026-10-01 to 2026-10-04, with received_rows values of 10, 20, 15, 30 and accepted_rows of 1, 2, 3, 4 — give me both the string normalisation report and the deduplication report.","exampleUseCases":[{"title":"ETL pipeline duplicate detection","prompt":"I have 50 rows from our nightly ETL batch — each has a row_id, a dataset_group name, a date, and counts for received_rows and accepted_rows. Can you run exact row deduplication and string normalisation on them and give me both reports so I can see what got flagged?"},{"title":"Data quality audit before ingestion","prompt":"Before we load today's ingestion batch into the warehouse, can you normalise the dataset_group strings and detect any exact duplicate rows across the 120 records I'm sending? Dates range from 2026-11-01 to 2026-11-05, row IDs are prefixed with 'batch-nov'."},{"title":"Ad-hoc deduplication for analyst team","prompt":"Our analyst team exported about 80 rows from the ingestion log with row_id, dataset_group, date, received_rows, and accepted_rows columns — can you clean up the strings and pull a deduplication report so they know which rows are exact repeats?"}],"resultDescription":"Returns 2 analytical reports generated from the supplied data: (1) a string normalisation report detailing how dataset_group and other string fields were normalised across the submitted rows, and (2) an exact row deduplication report identifying which rows are exact duplicates based on all fields. No external lookups or live data are involved; all analysis is performed locally on the submitted records.","failureModes":["Submitting more than 200 rows returns a validation error (maxItems exceeded)","Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) on any row causes rejection","Invalid date format (not YYYY-MM-DD) fails pattern validation","row_id exceeding 80 characters is rejected","Numeric values outside ±1,000,000,000,000 fail min/max validation","Empty rows array (minItems: 1 not met) returns an error"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local string normalisation and exact row deduplication on data ingestion batch records (received_rows, accepted_rows) without any live lookups or external data enrichment. It is ideal for quick data quality checks on ETL/pipeline batches of up to 200 rows at minimal cost ($0.01 USDC for 2 reports). Prefer alternatives if you need fuzzy deduplication, semantic matching, large-scale batch processing beyond 200 rows, or integration with external data sources.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:26.453Z","isFirstParty":false,"canonicalSlug":"data-ingestion-batches-string-normalisation-exact-row-deduplication-9835a5bc"}