Federated Query Engine for Decentralized Data Analysis
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Solution Overview
Problem
Current enterprise information security architectures face challenges in efficiently analyzing and aggregating decentralized data from multiple sources due to the need for structured inputs and lack of a unified interface for real-time cross-referencing across various data storage locations, which is cumbersome and requires extensive user training.
Innovation Solution
A parallel and distributed query engine for federated searching is implemented as a cloud-based SAAS solution, providing a unified API that allows users to interact with multiple data storage locations using natural language processing and workflow-based operations, enabling real-time analysis and visualization of data from various sources without requiring data displacement or combination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If data is aggregated into a single location for analysis, then data analysis can be performed centrally, but data displacement and combination requirements increase system complexity and time requirements
Solution Approach 1:
The patent introduces a federated search system as an intermediary layer between users and decentralized data sources. This mediator enables centralized query management and result aggregation without requiring physical data movement, thus simplifying the system architecture while maintaining data accessibility.
Solution Approach 2:
The system segments the data analysis function into two parts: query execution at decentralized data sources and result aggregation at the federated search interface. This segmentation eliminates the need to centralize data storage while preserving analytical capabilities.
2Measurement precision
If structured search commands are used, then search precision can be maintained, but user training requirements and operational complexity increase
Solution Approach 1:
The federated search system provides multiple interfaces for user interaction, including both structured query language support and natural language processing capabilities. This multi-functionality allows users with varying skill levels to perform accurate searches without requiring extensive training on complex query syntax.
3Productivity
If multiple data sources are queried simultaneously, then real-time analysis capability is improved, but query engine complexity and resource requirements increase
Solution Approach 1:
The query engine dynamically adapts its execution strategy based on the number and type of data sources. It can automatically parallelize queries across multiple sources when resources are available, or sequence them when constraints exist, thus achieving real-time analysis without requiring a permanently complex engine architecture.
4Reliability
If data is stored in decentralized locations, then data security and availability are improved, but unified access and cross-referencing capabilities deteriorate
Solution Approach 1:
The federated search system provides a universal access interface that works across multiple decentralized data sources with different storage architectures and access protocols. This single interface maintains data availability benefits while restoring unified access capabilities through standardized query handling and result presentation.
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.