Unified Data Storage System for Business Intelligence Extraction
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Solution Overview
Problem
Current data analysis systems face challenges in efficiently extracting business intelligence from diverse and distributed data sources within organizations, often requiring multiple interfaces and incurring high overhead, while also needing to handle security and access restrictions.
Innovation Solution
A data storage system operated by a service provider that aggregates data from various sources, performs analysis, and provides business intelligence to clients through a single interface, allowing access at any time while enforcing security policies and reducing overhead by storing and processing data in a unified manner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If data is stored and analyzed in distributed systems across multiple interfaces, then data accessibility and client control are improved, but system complexity and overhead increase
Solution Approach 1:
The patent consolidates multiple distributed data systems and interfaces into a single unified data store managed by a service provider. This merging eliminates the need for clients to interact with multiple separate systems, reducing system complexity while maintaining data accessibility through a single standardized interface.
Solution Approach 2:
The service provider acts as an intermediary between clients and the underlying data infrastructure. This mediator manages the complexity of data storage, format conversion, and analysis operations, allowing clients to access data without needing to understand or manage the complex distributed systems beneath.
2Adaptability or versatility
If multiple interfaces are used to access diverse data sources, then data source compatibility is improved, but overhead and processing time increase
Solution Approach 1:
The unified data store implements a universal interface that can handle multiple data formats and sources through a single standardized access point. This multi-functional interface supports various data types and operations without requiring separate access mechanisms for each data source, improving both compatibility and efficiency.
Solution Approach 2:
The service provider performs preliminary data processing, format standardization, and validation before data is stored in the unified data store. This advance preparation eliminates the need for real-time format conversion and processing when clients access the data, significantly improving processing efficiency.
3Reliability
If data is processed and stored in proprietary formats by distinct systems, then system-specific functionality is preserved, but integration difficulty and access complexity increase
Solution Approach 1:
The system preserves local data format characteristics and proprietary functionalities at the source systems while introducing a standardized interface at the unified data store level. Each data source maintains its local quality and specific functionality, but the integration layer provides standardization without requiring changes to the underlying systems.
4Productivity
If continuous data analysis is performed by the service provider, then business intelligence extraction is improved, but data access control and security management become more complex
Solution Approach 1:
The service provider implements automated security policies and access control mechanisms that operate autonomously without requiring manual intervention. The system self-manages data access permissions, analysis authorization, and security enforcement, reducing the complexity of security management while enabling continuous business intelligence extraction.
Data Source
AI summary
Among other things, an aspect includes a data storage system associated with a provider entity and storing data on behalf of a client entity, the data being accessible from the data storage system by the client entity, a data interface enabling access by the provider entity to the data of the data storage system, and an analysis engine maintained by the provider entity to, at times determined by the analysis engine, access the data using the data interface, analyze the data, and generate results of the analysis for use by the client entity.