Data Product Compatibility Checking for Version-Safe Modifications

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Solution Overview

Problem

Existing data product development methods fail to ensure compatibility between modifications and existing versions, leading to unintended integration failures and unnecessary computational overheads due to the disconnect between software and data engineering skills.

Innovation Solution

A method that automatically determines compatibility of user-specified modifications with existing data product versions, triggering failure events or providing feedback to prevent breaking changes, ensuring iterative refinement without disrupting downstream consumers.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If data product modifications are made iteratively to improve functionality, then the data product can be refined and enhanced, but compatibility with existing versions may be broken causing integration failures

Engineering Contradiction:

Improvedata product refinement capabilityVSAvoidintegration stability

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system performs preliminary compatibility checking before applying modifications to the data product. The compatibility determination module analyzes proposed changes against the data product schema and version history to predict compatibility issues in advance, preventing breaking changes before they occur.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system provides feedback to developers about compatibility issues when modifications are attempted. The compatibility determination module generates feedback information that indicates whether proposed changes are compatible with existing versions, allowing developers to adjust their modifications accordingly.

Inventive Principle:

Principle #23Feedback

2Reliability

If validation or double-checking functionality is added to data consumer processes, then data reliability can be improved, but computational resource consumption increases

Engineering Contradiction:

Improvedata trustworthinessVSAvoidcomputational resource consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system introduces a compatibility determination module as an intermediary between data product developers and consumers. This module automatically ensures compatibility of modifications, acting as a mediator that prevents breaking changes without requiring validation logic in consumer processes.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The data product system performs self-validation through automated compatibility checking. The compatibility determination module independently verifies that modifications maintain compatibility with existing versions, eliminating the need for consumer processes to perform manual validation or double-checking.

Inventive Principle:

Principle #25Self-service

3Reliability

If automated compatibility checking is implemented, then integration failures can be prevented, but development process complexity increases

Engineering Contradiction:

Improveintegration stabilityVSAvoiddevelopment process complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The compatibility determination module operates as a self-service component within the data product development platform. It automatically performs compatibility analysis without requiring manual intervention or complex configuration, simplifying the development process while maintaining reliability.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system manages complexity by focusing on key compatibility parameters such as schema changes, data type modifications, and constraint violations. The compatibility determination module analyzes these critical parameters to assess compatibility, avoiding the need to evaluate all possible system configurations.

Inventive Principle:

Principle #35Parameter changes

4Reliability

If manual verification of data compatibility is performed, then compatibility can be ensured, but developer workload and time consumption increase

Engineering Contradiction:

Improvecompatibility assuranceVSAvoiddeveloper time consumption

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The compatibility determination module performs automated self-verification of data product compatibility. It automatically analyzes modifications against the data product schema and version history, eliminating the need for manual verification by developers and significantly reducing time consumption.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system replaces manual mechanical verification processes with automated computational analysis. The compatibility determination module uses algorithmic comparison of data schemas and versions to assess compatibility, substituting human manual checking with automated mechanical processes that are faster and more consistent.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20250342148A1Data product development, systems and methods

Publication Date: 2025.11.06 FAIR ISAAC & CO INC

AI summary

This disclosure relates to methods, devices, and computer-readable media for use in developing data products. One such method comprises receiving an existing build of the data product, identifying a data product version associated with the existing build, receiving a user-specified modification for the data product, in response to a user input, automatically determining a compatibility result for the modification with the identified data product version, based on the existing build of the data product, and in response to the determined compatibility result being a negative compatibility result, triggering a failure event in relation to the identified data product version.