Hierarchical IT Architecture Visualization Engine
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Solution Overview
Problem
Organizations face challenges in understanding and managing their IT architecture due to complex, interdependent structures that are difficult to analyze and modify, leading to misconceptions about implemented functionalities, lack of clear relationships between IT architecture and business demands, and inefficient planning for change programs.
Innovation Solution
A computerized system for capturing, aggregating, and visualizing structural data using a structured, hierarchical model that includes a data capture engine, display engine, and graphical user interface engine to provide a systematic analysis and clear visualization of IT architectures, enabling IT managers to make informed decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a structured, hierarchical model is used to capture and aggregate IT architecture data, then the clarity and understandability of architectural relationships is improved, but the complexity of the data capture and processing system increases
Solution Approach 1:
The patent segments the complex IT architecture data into a hierarchical model with multiple levels (enterprise level, business level, application level, technology level). This segmentation allows the system to manage and visualize complex relationships by breaking them down into manageable hierarchical components, reducing information loss while maintaining systematic organization.
Solution Approach 2:
The patent introduces a data capture engine and visualization engine as intermediary components between the raw architecture data and the users. These intermediaries process, aggregate, and present the data in a structured hierarchical format, managing the complexity of data capture while delivering clear architectural relationships to users.
2Measurement precision
If detailed structural data of IT architecture is captured and analyzed, then the accuracy of decision-making is improved, but the time and resources required for analysis increase
Solution Approach 1:
The patent implements preliminary action by pre-establishing the structured hierarchical model framework and pre-configuring the data capture engine with standardized data collection templates. This preparation work is done in advance, so when actual architecture data needs to be analyzed, the system can quickly capture and process information within the pre-defined structure, reducing analysis time while maintaining accuracy.
Solution Approach 2:
The patent uses visualization engines to create graphical copies and representations of the architecture data. Instead of analyzing raw data directly, the system generates visual models and diagrams that replicate the architectural relationships, enabling faster analysis and understanding while maintaining measurement precision through the structured model.
3Adaptability or versatility
If the IT architecture is frequently updated to reflect business changes, then the adaptability of the system is improved, but the reliability of existing architectural documentation deteriorates
Solution Approach 1:
The patent implements a dynamic data capture engine that can be updated and reconfigured as business needs change. The hierarchical model structure allows for adding, removing, or modifying elements at different levels without affecting the entire system. This dynamic capability enables the architecture to adapt to business changes while maintaining reliable documentation through the structured framework that tracks all changes systematically.
Solution Approach 2:
The patent incorporates feedback mechanisms where the data capture engine continuously monitors and captures changes in the IT architecture. This feedback loop ensures that the architectural documentation remains reliable and up-to-date by automatically detecting and recording modifications, maintaining accuracy even as the system evolves to meet changing business requirements.
4Loss of information
If comprehensive data about all architectural components and their interrelationships is collected, then the completeness of the architectural overview is improved, but the difficulty of managing and visualizing the data increases
Solution Approach 1:
The patent segments comprehensive architecture data into a hierarchical structure with distinct levels (enterprise, business, application, technology). This segmentation organizes the complete dataset into manageable sections, allowing the system to maintain completeness of the architectural overview while reducing the difficulty of managing and visualizing the data through structured decomposition.
Solution Approach 2:
The patent adds a hierarchical dimension to the data organization, transforming flat comprehensive data into a multi-dimensional hierarchical structure. This dimensional change enables the system to manage and visualize complete architectural information more effectively by providing multiple levels of abstraction and organization, making the data more manageable while maintaining completeness.
Data Source
AI summary
Computerized techniques, systems, and computer program products for a structured, hierarchical model for capturing, aggregating, and/or visualizing structural data of architectures of technical equipment (e.g., IT architectures). The techniques, systems and/or computer program products may include at least one data capture engine adapted to capture and aggregate data based on a structured, hierarchical model; a display engine to generate a plurality of different displays of the captured data in dependency of the structured hierarchical model, where the data capture engine includes at least one database to store the data according to the structured, hierarchical model.