Autonomous Data Pipeline Comparator for Production Validation

The system performs preliminary comparison of data pipeline outputs by capturing and storing reference data from the old pipeline before the new pipeline is fully deployed. This preliminary action enables subsequent validation of the new pipeline against the stored reference data, allowing detection of data quality issues that would not be visible in isolated test environments.

The patent introduces an intermediary validation layer that sits between the new data pipeline and the production data warehouse. This intermediary component captures output data from both the old and new pipelines, performs automated comparison, and validates data quality metrics without requiring direct access to live production data, thus resolving the contradiction between safety and detection precision.

Before decommissioning the old pipeline, the system performs preliminary validation by comparing a subset of data pipeline outputs from the new pipeline against stored reference data from the old pipeline. This preliminary action establishes confidence metrics that enable safe decommissioning of the old pipeline while maintaining system simplicity.

The patent implements partial validation by comparing only critical data fields and metrics rather than entire data sets. This partial action approach provides sufficient confidence for pipeline decommissioning while minimizing the complexity and overhead of the validation process, enabling the old pipeline to be decommissioned safely.

The system extracts and captures only the necessary output data from the data pipeline for comparison purposes, rather than processing entire live data sets. This extraction approach enables validation against live data while minimizing data volume and legal compliance burdens by taking out only the critical fields needed for validation.

The patent creates copies of reference data from the old pipeline and stores them in a validation data store. These copies enable comparison and validation of the new pipeline without requiring access to actual live production data, thus maintaining data quality confidence while avoiding data volume and compliance issues.

The system implements self-service automated validation that compares data pipeline outputs without requiring manual intervention. The automated process handles customized domain object models by using configurable comparison rules that adapt to different data structures, eliminating time-consuming manual validation while maintaining adaptability to customizations.

The patent enables parameter changes in the validation process by allowing configurable comparison rules, thresholds, and data field selections. These parameter changes allow the system to adapt to customized domain object models and different validation requirements automatically, reducing time consumption while maintaining versatility.