Virtual Data Lake for Decentralized Enterprise 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, requiring structured inputs and trained personnel, and lack a unified interface for real-time analysis across multiple storage locations.
Innovation Solution
A virtual data lake system with browser-based decentralized data access and analysis, providing a single API for simultaneous access and analysis of multiple enterprise data storage locations, incorporating interactive AI, natural language processing, and workflow-based operations, allowing text, voice, and visual interactions, and integrating with existing SIEM and cloud platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is aggregated into a single location for analysis, then data analysis efficiency is improved, but data security and decentralized access control are worsened
Solution Approach 1:
The patent introduces a virtual data lake as an intermediary layer that sits between decentralized data sources and analysis tools. This virtual layer enables unified data access and analysis without physically aggregating sensitive data, thus maintaining data security while improving analysis efficiency. The virtual data lake mediates between the need for centralized analysis and the requirement for decentralized data retention.
Solution Approach 2:
The system segments data access into different virtual environments within the virtual data lake, allowing different users and systems to access specific data subsets according to their needs and security clearances. This segmentation enables efficient analysis for authorized users while maintaining the decentralized and secure storage architecture.
2Loss of information
If multiple data storage locations are accessed simultaneously, then data analysis comprehensiveness is improved, but system complexity increases
Solution Approach 1:
The virtual data lake provides a universal interface that can access and query multiple decentralized data storage locations through a single unified system. This multi-functional platform handles diverse data sources, query types, and user requirements through one standardized access point, reducing system complexity while maintaining comprehensive data analysis capability.
Solution Approach 2:
The virtual data lake acts as a mediator that abstracts the complexity of accessing multiple data storage locations. It provides a unified query interface that automatically manages the complexity of data retrieval from multiple sources, allowing users to access comprehensive data without directly dealing with the underlying system complexity.
3Measurement precision
If structured search commands are required for data analysis, then data query precision is improved, but ease of use is worsened
Solution Approach 1:
The system dynamically adapts between structured and unstructured query modes. It accepts both natural language queries from users and structured commands from analytical tools, automatically translating and processing them appropriately. This dynamic approach maintains query precision while significantly improving ease of use for different user types.
Solution Approach 2:
The virtual data lake changes the parameter of query structure flexibility, allowing the same system to accommodate both rigid structured commands (for precision) and flexible natural language queries (for ease of use). It transforms queries between different structural forms based on the input type, maintaining precision across different interaction modes.
Data Source
AI summary
A virtual data lake system created with browser-based decentralized data access and analysis is disclosed herein. As contemplated by the present disclosure, the system provides a single 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 allows a user to analyze and cross-reference data stored in multiple locations in real time without requiring the actual data files to be displaced or combined. The system further implements interactive artificial intelligence, natural language processing, and workflow-based operations for improved user access and functionality.