Associative Data Indexing for Interactive Analysis of Large Datasets
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Solution Overview
Problem
Existing data analysis systems struggle with managing and analyzing large datasets efficiently, particularly in closed environments, and lack interactive and associative capabilities for user-driven data exploration and external processing integration.
Innovation Solution
The system employs an associative data indexing engine that loads data in-memory, generates graphical objects, and performs calculations using an inference engine, allowing user-driven selection and external processing through an interface, while maintaining a state space for dynamic data management and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is stored and processed in traditional disk-based systems, then storage capacity is sufficient for large datasets, but data access speed and analysis efficiency deteriorate
Solution Approach 1:
The patent segments the data processing system into multiple components: in-memory storage for active data, disk storage for archival data, and distributed computing nodes for parallel processing. This segmentation allows fast access to frequently used data while maintaining capacity for large datasets through hierarchical storage and distributed architecture.
2Measurement precision
If complex calculations are performed on large datasets, then analysis depth increases, but processing time and computational resources worsen
Solution Approach 1:
The patent implements preliminary action through pre-computation of aggregate statistics, maintenance of in-memory data structures for quick querying, and pre-loading of frequently accessed data into memory. These preliminary preparations enable complex analyses to be performed faster when needed, reducing processing time while maintaining analysis depth.
3Adaptability or versatility
If user-driven interactive exploration is enabled, then data discovery capability improves, but system complexity and computational overhead worsen
Solution Approach 1:
The patent applies dynamics by creating a flexible, adaptive system that responds to user interactions in real-time. The architecture dynamically adjusts data retrieval strategies, recomputes analyses based on user selections, and updates visualizations interactively. This dynamic behavior enables versatile data discovery while managing complexity through event-driven architecture and incremental computation.
Data Source
AI summary
The present disclosure relates to computer implemented methods and systems for data management, data analysis, and processing. The disclosed methods and systems can incorporate external data analysis into an otherwise closed data analysis environment.