Analytic Process Design via Modular GUI Components

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Solution Overview

Problem

Conventional solutions for data analysis in enterprises are time-intensive, expensive, and often have performance and reliability issues, limiting the effectiveness of real-time data analysis due to the complexity of disparate data systems and formats.

Innovation Solution

A system and method for visually designing analytics processes using a graphical user interface (GUI) that allows for efficient configuration and execution of data analysis processes, enabling real-time data processing and visualization across multiple data sources.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If custom analytic applications are developed for each system, then the analysis can be tailored to specific needs, but the development time and cost increase significantly

Engineering Contradiction:

Improvecustomization capabilityVSAvoiddevelopment time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The analytic application is divided into reusable modular components that can be independently developed, configured, and assembled. Each component handles a specific function (data access, transformation, analysis, visualization), allowing rapid composition of customized analytics without developing entire applications from scratch.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

A universal component library provides multi-functional building blocks that can be applied across different analytic scenarios. The same component framework serves multiple purposes through configuration rather than custom development, enabling one-size-fits-many solutions while maintaining adaptability.

Inventive Principle:

Principle #6Universality (Multi-functionality)

2Adaptability or versatility

If custom analytic applications are developed, then specific analysis needs are met, but the cost and resource requirements increase

Engineering Contradiction:

Improvecustomization capabilityVSAvoiddevelopment cost

Core Design Contradiction:

Adaptability or versatilityVSEase of manufacture

Solution Approach 1:

Pre-built analytic components and templates serve as reusable copies that can be instantiated multiple times with different configurations. Instead of creating new applications for each need, existing components are copied and adapted through parameter settings, dramatically reducing development cost and resource requirements.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

Customization is achieved through changing parameters and configuration settings of existing components rather than modifying their core functionality. This allows extensive adaptability while maintaining efficient, standardized component implementations that are cost-effective to deploy.

Inventive Principle:

Principle #35Parameter changes

3Adaptability or versatility

If custom analytic applications are used, then specific requirements are addressed, but performance and reliability issues arise

Engineering Contradiction:

Improvecustomization capabilityVSAvoidperformance stability

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

By segmenting the analytic application into standardized components with well-defined interfaces and responsibilities, reliability is improved through modular testing, easier debugging, and reduced complexity. Each component can be independently validated and replaced without affecting the entire system.

Inventive Principle:

Principle #1Segmentation

4Productivity

If conventional custom solutions are implemented, then analysis capabilities are provided, but real-time processing capability is limited

Engineering Contradiction:

Improveanalysis capabilityVSAvoidreal-time processing speed

Core Design Contradiction:

ProductivityVSSpeed

Solution Approach 1:

Analytic components are pre-configured and prepared in advance with optimized processing logic. Data pipelines are established beforehand, and transformation rules are predefined, enabling real-time processing when data arrives without the overhead of runtime decision-making or ad-hoc processing.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS9235316B2Analytic process design

Publication Date: 2016.01.12 ACCENTURE GLOBAL SERVICES LTD

AI summary

Embodiments of the present invention are directed to a method and system for developing an analytic process. The method includes displaying, within an electronic system, a plurality of components operable to be used for designing a data analysis process. A user makes a selection of a data access component from the plurality of components. The data access component is operable for configuring access to a data source. The method further includes the user making a selection of a data selection component from the plurality of components and a data display component. The data selection component is operable for selecting data accessed via the data access component. The data display component is operable for configuring display of data based on the data selection component. Configuration data corresponding to the data access component, the data selection component, and the data display component can then be stored.