{"uid":"cap_tYe0bgumhzvBpNOZigIT5","slug":"transformation-throughput-iqr-outlier-flags-and-keyed-dataset-bf2a5741","name":"Transformation Throughput IQR Outlier Flags and Keyed Dataset Comparison","description":"Transformation throughput — IQR outlier flags + Keyed dataset comparison: IQR outlier flags + Keyed dataset comparison for supplied transformation throughput records (processed_rows, duration_seconds). Up to 200 rows; 2 independent reports using shared local analytical engines. 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I have the pre-deployment and post-deployment run logs with row_id, dataset_group, date, processed_rows, and duration_seconds. Can you compare the two datasets and flag any IQR outliers in duration_seconds so I can see if performance regressed?"},{"title":"Data group throughput audit","prompt":"I need to audit throughput across our group-a and group-b transformation jobs for October. Here are 80 rows of records — please run IQR outlier flags on processed_rows and do a keyed comparison between the two groups so I can spot which specific jobs are behaving differently."}],"resultDescription":"Returns two independent reports: (1) an IQR outlier flags report identifying which rows fall outside the interquartile range for the selected field (processed_rows or duration_seconds), and (2) a keyed dataset comparison report highlighting differences between the primary and secondary datasets matched by row_id.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows supplied — request rejected","Missing required fields (row_id, dataset_group, date, processed_rows, duration_seconds) — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Numeric values out of allowed range — validation error","Mismatched or missing keys between primary and comparison datasets may result in sparse comparison report"],"whenToPreferThis":"Choose this endpoint when you need both IQR-based outlier detection and a keyed cross-dataset comparison on transformation throughput records in a single low-cost call. 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