Natural-Language Parallel Query Engine for Federated Data Analysis
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Solution Overview
Problem
Existing enterprise information security architectures face challenges in efficiently analyzing decentralized data across multiple locations without requiring data aggregation, necessitating structured command-line inputs and trained users, which limits the effectiveness of security analysis.
Innovation Solution
A parallel and distributed query engine with a cloud-based interface that allows users to analyze and cross-reference data from multiple sources using natural language processing and workflow-based operations, interacting with existing platforms like SIEM and cloud services, while obfuscating personally identifiable information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in decentralized locations across multiple platforms, then data security and distribution are improved, but the ability to analyze and cross-reference data in real time deteriorates
Solution Approach 1:
The patent introduces a natural language processing intermediary that mediates between the user and decentralized data sources. The NLP engine translates natural language queries into platform-specific search commands, enabling unified access to distributed data without requiring data aggregation or user knowledge of multiple query languages.
Solution Approach 2:
The system implements a universal natural language interface that works across multiple decentralized data platforms simultaneously. This single interface can query different data sources using their respective query languages while presenting unified results, eliminating the need for separate tools for each platform.
2Measurement precision
If structured command-line inputs are required for data analysis, then analysis precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent replaces the mechanical system of structured command-line inputs with a natural language processing system. Instead of requiring users to type precise syntax commands, the system uses NLP to interpret conversational queries and translate them into effective search operations, maintaining analysis precision while dramatically improving ease of operation.
Solution Approach 2:
The system changes the parameter of user input from structured syntax to natural language. By transforming the input format parameter, the system maintains the precision needed for accurate data analysis while making the interface accessible to users without specialized training.
3Reliability
If users require training to effectively use security analysis platforms, then analysis effectiveness is improved, but productivity deteriorates
Solution Approach 1:
The natural language processing system provides self-service capabilities that allow users to perform complex security analyses without external training. The system automatically handles query translation, result aggregation, and presentation, enabling users to achieve effective analysis immediately without a learning curve.
4Loss of information
If data must be aggregated into a single location for analysis, then analysis unified view is improved, but loss of time and resources deteriorates
Solution Approach 1:
The patent extracts the data aggregation step from the analysis process. Instead of requiring physical or virtual consolidation of data into a single location, the system extracts and translates queries to execute directly at distributed data sources, then aggregates only the results. This eliminates time-consuming data movement while maintaining a unified analytical view.
Data Source
AI summary
A parallel and distributed query engine for federated searching is disclosed herein. As contemplated by the present disclosure, the system may provide a single application programming interface that allows a user to access and analyze multiple enterprise data storage locations remotely and simultaneously while presenting and reporting information from the multiple sources in a single, uniform display. Such a solution may allow a user to analyze and cross-reference data stored in multiple locations by using multiple queries in real time without requiring the actual data files to be displaced or combined. The system may further implement interactive artificial intelligence assistant, natural language processing, and workflow-based operations for improved user access and functionality.