Data Object Validation via Shadow Processing and Segmentation

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Solution Overview

Problem

Inaccessibility of data objects during processing and the need for manual reviews to identify errors lead to inefficiencies and variable processing times, especially when dealing with large numbers of data objects.

Innovation Solution

A dashboard monitor in a processing center core layer initiates monitoring of data objects for changes, recording them in a changed objects list, and a daemon framework orchestrates compliance validation with policies, providing real-time results to a user interface dashboard, with a shadow processing component validating compliance based on validation rules and alerting users to noncompliance issues.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If data objects are frozen during processing, then data integrity is maintained, but data accessibility for editing and viewing is lost

Engineering Contradiction:

Improvedata integrityVSAvoiddata accessibility

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system segments data objects into two versions: frozen original data objects for processing integrity and shadow copies for validation and review. This allows the original data to remain frozen while shadow copies can be accessed and validated without compromising data integrity.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Shadow processing components act as intermediaries between the frozen data objects and the validation requirements. These shadow copies serve as mediators that can be reviewed and validated without directly accessing or modifying the frozen original data, thus maintaining both integrity and accessibility.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If manual reviews by human capital assets are used, then error detection capability is improved, but processing time increases significantly

Engineering Contradiction:

Improveerror detection capabilityVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary automated validation of shadow processing components against compliance policies before human review. This preliminary action filters out obvious errors and validates straightforward cases, reducing the burden on human reviewers and accelerating overall processing time while maintaining thorough error detection.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements automated feedback loops where validation results from shadow processing components are immediately compared against compliance policies. This automated feedback provides rapid error detection for clear-cut cases, reserving human capital assets for complex or ambiguous cases that require expert judgment.

Inventive Principle:

Principle #23Feedback

3Manufacturing precision

If comprehensive validation of all data objects is performed, then compliance accuracy is improved, but processing throughput decreases

Engineering Contradiction:

Improvecompliance accuracyVSAvoidprocessing throughput

Core Design Contradiction:

Manufacturing precisionVSProductivity

Solution Approach 1:

The system applies partial validation action by validating shadow processing components rather than all possible data objects. This selective validation approach maintains compliance accuracy for critical shadow copies while avoiding the excessive processing time that would result from validating every single data object, thus preserving processing throughput.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS10430259B2Data object validation using multilayer computing environments

Publication Date: 2019.10.01 SAP SE

AI summary

Systems and methods are provided for data object validation using multilayer computing environments. A dashboard monitor initiates monitoring of a listener component belonging to a processing center core layer for changes in data objects stored in a data store. The listener component monitors a data maintenance component for changed data objects recorded in a changed objects list stored within the listener component. A daemon framework orchestrates compliance validation of the changed data objects with policies stored in another data store. Compliance of the changed data objects with the policies based on validation rules is validated by a shadow processing component. Real time results associated with the validated compliance are provided to a user interface dashboard.