Relationship Tree Model for Data Insight Synchronization

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Solution Overview

Problem

Businesses face the challenge of time-consuming and inaccurate data analysis updates when raw data changes, leading to incorrect insights in IT systems, as traditional methods require re-running the entire analysis process to maintain synchronization between raw data and insights.

Innovation Solution

A system with a synchronization component that generates a relationship tree model, scans data fields at each stage of the data analysis process, and updates insights accordingly, using data scaling and pre-defined rules to prune the model and ensure consistency between raw and insight data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional data analysis update methods are used, then accuracy of insights is maintained, but time consumption increases significantly

Engineering Contradiction:

Improveaccuracy of insightsVSAvoidtime consumption for updates

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent segments the data analysis process into distinct stages (data collection, processing, analysis, insight generation) and creates a relationship tree model that maps dependencies between data fields at each stage. This segmentation allows selective updating of only affected segments when raw data changes, rather than re-running the entire analysis process, thus reducing time consumption while maintaining insight accuracy.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary action by pre-establishing the relationship tree model that captures all dependencies between data fields before any updates occur. This pre-computed structure enables rapid identification of affected insights when data changes, eliminating the need for time-consuming full re-analysis while ensuring accuracy through systematic dependency tracking.

Inventive Principle:

Principle #10Preliminary action

2Reliability

If traditional data analysis update methods are used, then completeness of analysis is ensured, but productivity decreases

Engineering Contradiction:

Improvecompleteness of analysisVSAvoidproductivity of data analysis updates

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The patent implements feedback mechanisms through the relationship tree model that continuously monitors data field changes and automatically propagates updates through the analysis pipeline. When raw data changes, the system provides feedback by identifying affected data fields and insights, ensuring complete analysis coverage while dramatically improving productivity through automated, targeted updates rather than manual full-reanalysis.

Inventive Principle:

Principle #23Feedback

3Stability of the object's composition

If the entire data analysis process is re-run to update insights, then synchronization between raw data and insights is maintained, but complexity of the process increases

Engineering Contradiction:

Improvesynchronization between data and insightsVSAvoidcomplexity of update process

Core Design Contradiction:

Stability of the object's compositionVSDevice complexity

Solution Approach 1:

The patent introduces an intermediary relationship tree model that mediates between raw data and final insights. This intermediate structure captures dependencies without requiring full re-execution of the analysis process. When data changes, the intermediary model efficiently propagates updates only to affected insights, maintaining synchronization while reducing process complexity by eliminating redundant analysis steps.

Inventive Principle:

Principle #24Intermediary (Mediator)

4Measurement precision

If data fields are updated in complex IT systems, then accuracy of decision-making is maintained, but time and effort required increases

Engineering Contradiction:

Improveaccuracy of decision-makingVSAvoidtime and effort for updates

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent extracts and isolates the essential dependency relationships into a separate relationship tree model, taking out the complex synchronization logic from the main data analysis workflow. This extraction allows rapid updates to be performed using only the extracted dependency structure, maintaining decision-making accuracy through systematic update propagation while significantly reducing the time and effort required compared to re-running complex analysis processes.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS11120041B2Maintaining synchronization of collected data and insights

Publication Date: 2021.09.14 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

In an approach for maintaining data synchronization, a processor scans a set of data fields at each stage of a data analysis process. A processor generates a relationship tree model, wherein the set of data fields each correspond to a node in the relationship tree model. A processor prunes the relationship tree model. Responsive to an update to a data field of the set of data fields, a processor promulgates the update using the relationship tree model to generate an updated set of insight data. A processor outputs the updated set of insight data.