Data Reconciliation Using Bridge Members for Faster Auditing
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Solution Overview
Problem
Conventional data reconciliation techniques are expensive, time-consuming, and error-prone, failing to efficiently verify data integrity during or after migration, updates, or changes, and often miss issues that require manual detection and correction.
Innovation Solution
A data reconciliation controller that aligns dimensions from multiple datasets using bridge members, refreshes combination dimension members based on execution delimiters, generates reconciliation reports, and provides graphical user interfaces for error exposure and auditing, allowing for efficient and rapid identification of discrepancies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional data reconciliation techniques are used, then data verification is performed, but the process is expensive, time-consuming, and error-prone
Solution Approach 1:
The patent segments the data reconciliation process into distinct phases: data extraction from multiple sources, transformation to a standardized format, loading into a reconciliation database, and analysis/generation of reconciliation reports. This segmentation allows each phase to be optimized independently and enables parallel processing where applicable, reducing overall reconciliation time while maintaining accuracy through systematic verification at each stage
Solution Approach 2:
The patent introduces an intermediary reconciliation database and standardized data format that acts as a mediator between multiple source systems. This intermediary layer transforms diverse data formats into a common structure, enabling efficient comparison and reconciliation without requiring direct complex interactions between all source systems, thereby reducing processing time and errors
2Reliability
If conventional data reconciliation techniques are used, then data verification is performed, but the process is expensive
Solution Approach 1:
The patent creates copies of data from multiple source systems and loads them into a centralized reconciliation database in standardized format. This copying approach allows simultaneous analysis of all source data without requiring expensive direct connections or real-time access to all source systems, reducing infrastructure costs while maintaining verification accuracy through comprehensive data comparison
3Measurement precision
If comprehensive data reconciliation is performed, then accuracy is improved, but complexity of the process increases
Solution Approach 1:
The patent transforms diverse data parameters from multiple source systems into a standardized format with consistent data types, structures, and validation rules. This parameter standardization enables comprehensive comparison and verification across all sources while simplifying the reconciliation process through uniform data handling procedures, thereby improving accuracy without proportionally increasing complexity
Data Source
AI summary
A method includes receiving a data reconciliation request requesting data reconciliation for a first dataset and a second dataset. The method also includes obtaining the first dataset including one or more dimensions each having a plurality of dimension members and obtaining the second dataset including one or more dimensions each having a plurality of dimension members. For each dimension of the first dataset, the method includes obtaining a bridge member that associates the respective dimension of the first dataset with a dimension of the second dataset. The method includes generating a first and second set of combination dimension members and refreshing the first and second set of combination dimension members using an execution delimiter value. The method includes generating, using the refreshed first and second set of combination dimension members, a third set of combination dimension members to generate a data reconciliation report.