Automated Data Reconciliation Across Disparate Storage Devices
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Solution Overview
Problem
Conventional systems for reconciling data stored in disparate data storage devices are burdensome, costly, and error-prone, requiring manual review of spreadsheets and extensive operational resources.
Innovation Solution
A computer-implemented method and system that automatically identifies and displays differences between data stored in disparate data storage devices by loading data into a repository, identifying discrepancies, and generating a visual output indicating these differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual review of spreadsheets is used to identify data differences, then data reconciliation can be performed, but operational expenses and errors increase
Solution Approach 1:
The patent replaces the manual mechanical review process with an automated computer-implemented system that loads data from disparate storage devices, identifies differences programmatically, and generates visual outputs. This substitution eliminates manual labor while maintaining high data accuracy through systematic automated comparison.
Solution Approach 2:
The system enables self-service data reconciliation by automatically performing data loading, comparison, and difference identification without requiring manual intervention. The automated generation of visual outputs with highlighted differences allows users to independently reconcile data across storage devices.
2Measurement precision
If individual file inspection is performed to identify data differences, then data discrepancies can be detected, but time and operational resources are consumed
Solution Approach 1:
The patent merges multiple individual file inspections into a single automated process that loads and compares data from numerous files simultaneously. The system consolidates data from disparate storage devices into a unified comparison framework, identifying all differences in one operation rather than requiring sequential individual file review.
Solution Approach 2:
The automated system maintains continuous useful action by systematically loading, comparing, and identifying data differences across all files without interruption. The continuous automated process eliminates the stop-and-go nature of manual inspection, maintaining high detection precision while dramatically reducing total reconciliation time.
3Reliability
If comprehensive data reconciliation is performed across multiple storage devices, then data differences are identified, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary automated reconciliation system that mediates between disparate data storage devices. This intermediary system handles the complexity of data loading, format standardization, and comparison logic, presenting a simplified interface that generates visual outputs with clearly highlighted differences, thereby maintaining data consistency without exposing system complexity to users.
Data Source
AI summary
A method includes receiving a request to reconcile a first set of data stored in a first datastore and a second set of data stored in a second datastore, retrieving, from the first datastore, the first set of data, and retrieving, from the second datastore, the second set of data. The first set of data includes one or more first rows each including a respective first data value and the second set of data includes one or more second rows each including a respective second data value. The method also includes determining a mismatch between a respective one of the first data values and a respective one of the second data values. Based on determining the mismatch, the method also includes updating the respective one of the second data values to match the respective one of the first data values.