Data Reconciliation via Metadata Tagged Entries

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Solution Overview

Problem

Existing data classification systems face constraints such as rigid structures and manual conversion errors, limiting search and manipulation capabilities, and struggling with reconciliation due to inflexible data mapping.

Innovation Solution

A data management system that applies flexible rules for generating and manipulating posted entries using metadata tagging, routing payloads based on source and content, and employing machine learning models for classification and reconciliation policies to address discrepancies.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If rigid structures and manual conversion are used for data classification, then regulatory constraints are satisfied, but search and manipulation capabilities are limited and error-prone

Engineering Contradiction:

Improveregulatory constraint satisfactionVSAvoidsearch and manipulation capability

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The patent transforms rigid, static data classification structures into dynamic, flexible systems. The conversion engine dynamically generates posted entries from source data, and the search system dynamically queries this posted data using flexible criteria. This allows the system to adapt to both regulatory requirements and user search needs without being constrained by fixed structures.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent introduces an intermediary layer (the conversion engine and posted entry system) between source data and user queries. This intermediary transforms source data into a standardized posted entry format that satisfies regulatory constraints, while simultaneously enabling flexible search and manipulation capabilities through the search system that queries this intermediate representation.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If manual conversion logic is used, then regulatory constraints are met, but conversion errors occur and reconciliation is difficult

Engineering Contradiction:

Improveregulatory constraint satisfactionVSAvoidconversion accuracy

Core Design Contradiction:

ReliabilityVSManufacturing precision

Solution Approach 1:

The conversion engine performs self-service by automatically converting source data to posted entries using defined conversion rules, eliminating manual conversion errors. The system self-corrects and self-validates conversions against regulatory constraints, and the reconciliation system automatically identifies and flags discrepancies without manual intervention.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent implements feedback mechanisms where conversion results are automatically validated against regulatory constraints, and discrepancies are flagged for review. The reconciliation system provides feedback loops that identify conversion errors and allow for correction, improving conversion accuracy while maintaining regulatory compliance.

Inventive Principle:

Principle #23Feedback

3Stability of the object's composition

If rigid data mapping is used, then system structure is maintained, but reconciliation with ground truth sources is impossible

Engineering Contradiction:

Improvesystem structureVSAvoidreconciliation capability

Core Design Contradiction:

Stability of the object's compositionVSAdaptability or versatility

Solution Approach 1:

The patent segments the data system into distinct components: source data, conversion engine, posted entries, and reconciliation system. This segmentation allows each component to maintain its own structure and rules while enabling flexible mapping between them. The reconciliation system can independently compare posted entries with ground truth sources without disrupting the overall system structure.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces dynamic mapping capabilities that allow the reconciliation system to flexibly compare posted entries with ground truth sources from multiple candidate sources. The system can dynamically select which ground truth source to compare against based on the specific data being reconciled, maintaining system structure while enabling versatile reconciliation.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS11620309B2Data reconciliation and inconsistency determination for posted entries

Publication Date: 2023.04.04 TEKION CORP

AI summary

A system and a method are disclosed for receiving an entry, the entry comprising first content and a metadata tag corresponding to a classification, the first content populated by a first source. A rules engine determines that the first content comprises a data field associated with at least one of a plurality of reconciliation policies. Responsive to determining that the first content comprises a data field associated with at least one of the plurality of reconciliation policies, the rules engine selects a reconciliation policy based on the metadata tag. The rules engine retrieves, from a second source, second content associated with the data field, inputs the first content and the second content into a model, the model selected based on the reconciliation policy, the model generating an output, and performs a remediation action based on the output.