Hierarchical Dynamic Cataloging for Analytics Module Visualization
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Solution Overview
Problem
Conventional systems fail to provide effective visualization of analytics modules to various stakeholders within or outside an organization, limiting their ability to add value through ease of use and reusability across different applications and domains.
Innovation Solution
A processor-implemented method and system for hierarchical dynamic cataloging, which generates a hierarchical structure of inputs and stakeholders, performs mapping to identify relationships, and dynamically updates a catalog to enable reusability and zero coding dynamic algorithms, providing a dynamic view of algorithms and stakeholders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional systems are used for visualizing analytics modules, then the system structure remains simple, but the ease of use and reusability for multiple stakeholders deteriorates
Solution Approach 1:
The system segments analytics modules into a hierarchical structure with multiple levels of abstraction, allowing different stakeholders to view and interact with modules at appropriate granularities. This segmentation enables tailored visualization for different user roles while maintaining a manageable system architecture.
Solution Approach 2:
The patent introduces a hierarchical dimension to the system architecture, organizing analytics modules across multiple levels (e.g., domain level, application level, module level). This dimensional organization enables stakeholders to navigate and utilize modules according to their specific needs without overwhelming system complexity.
2Ease of operation
If analytics modules are customized for different stakeholders, then the ease of use improves, but the time and resources required for development increases
Solution Approach 1:
The system creates universal analytics modules that can serve multiple stakeholders and applications simultaneously. By designing modules with standardized interfaces and hierarchical organization, the same module can be reused across different contexts, eliminating the need for separate customizations for each stakeholder group.
Solution Approach 2:
The patent implements preliminary organization of analytics modules into a hierarchical catalog structure with standardized metadata and interfaces. This pre-organization enables stakeholders to quickly discover and reuse existing modules without requiring time-consuming customization, as the modules are already structured for multi-purpose utilization.
3Adaptability or versatility
If a hierarchical dynamic cataloging system is implemented, then the reusability of analytics modules improves, but the device complexity increases
Solution Approach 1:
The system implements a nested hierarchical structure where analytics modules are organized within progressively broader categories (e.g., specific modules nested within application domains nested within organizational structures). This nesting enables efficient reusability by allowing modules to be accessed at multiple hierarchical levels while maintaining a structured, manageable system architecture.
Data Source
AI summary
Data cataloging has become a necessity for empowering organizations with analytical ability. Conventional cataloging systems may fail to provide proper visualization of data to the different stakeholders of an organization. The present disclosure provides a hierarchical dynamic cataloging system so that visualization of data at different levels would be possible for different stake holders. In the present disclosure, a hierarchical structure of algorithms and multiple stake holders along with relevant metadata is generated. Further, a catalog is generated by performing a mapping across components comprised in the hierarchical structure and identifying relationship across the components based on mapping. The catalog gets dynamically updated and provides a dynamic view of the algorithms and associated metadata to the multiple stakeholders of an organization. Further, the disclosure supports reuse of already developed algorithms across multiple applications and domains resulting in optimization of resources and time.