Tag-Based Data Navigation for Large Dataset Exploration
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Solution Overview
Problem
Current IT data management systems face inefficiencies in searching and browsing large data sets due to their size and navigational limitations, constraining the ability to detect and resolve application and infrastructure issues effectively.
Innovation Solution
A data management system utilizing a graphical user interface with gesture-based navigation and tag-based filtering, allowing users to explore semi-structured data sets by designating a focal object and applying filters to traverse associated data objects, supported by engines such as a tag engine, associates engine, and filter engine to maintain and load relevant data for display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users search and browse through large data sets using traditional IT monitoring tools, then data can be analyzed, but the process is ineffective due to the size of the data set and navigational limitations
Solution Approach 1:
The patent segments large data sets into smaller, manageable visualizations that can be easily navigated. Instead of presenting the entire data set at once, the system divides it into discrete visual elements that users can explore incrementally through visual navigation, making large data analysis effective and operationally easy
Solution Approach 2:
The patent transitions from traditional tabular or chart-based data presentation to a visual exploration interface that adds spatial and interactive dimensions. Users can navigate data visually across multiple dimensions rather than linearly through tables, fundamentally changing how large data sets are accessed and analyzed
2Reliability
If strictly typed models with many details are used for data consumption, then data can be stored and analyzed, but user interface workflows and data constraints limit the ability to detect and resolve issues
Solution Approach 1:
The patent implements dynamic data exploration where the data model adapts to user needs rather than requiring users to conform to rigid schemas. The system allows flexible navigation and filtering of data without being constrained by pre-defined workflow paths, enabling adaptable issue detection while maintaining reliable data storage and analysis
Solution Approach 2:
The system allows users to dynamically change data presentation parameters and exploration criteria without being locked into fixed workflows. Users can modify how data is visualized and explored in real-time, enhancing adaptability for different issue detection scenarios while preserving the integrity of the underlying data model
Data Source
AI summary
In one implementation, a system for managing data includes a tag engine to maintain associations among objects of a data set, an associates engine to identify a first set of objects having a tag that matches a tag coupled to a focal object, a filter engine to identify a second set of objects based on the filter evaluated on the first set of objects, and a load engine to cause the second set of objects to load for display in a window of a UI.