Enterprise Data Classification via Access Metrics
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Solution Overview
Problem
Current data classification systems in enterprises face challenges in efficiently identifying and managing data of interest by relying solely on content-based identifiers, lacking effective non-content based data characterization and dynamic access metric adaptation, which limits their ability to prioritize and update data access permissions in real-time.
Innovation Solution
A method and system that characterize data of interest using both non-content based and content based identifiers, with dynamic access metrics, allowing for real-time redefinition of search fields and prioritization based on access metrics, and maintaining databases for access and metadata to facilitate near real-time data management and access permission modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data classification relies solely on content-based identifiers, then the system structure remains simple, but the ability to prioritize and manage data dynamically deteriorates
Solution Approach 1:
The data characterization approach is segmented into two independent components: content-based identifiers (traditional) and non-content-based identifiers (new). This segmentation allows the system to maintain simplicity in content handling while adding dynamic prioritization capability through separate access metric tracking, resolving the contradiction between adaptability and complexity.
Solution Approach 2:
The system adds a new dimension to data characterization by introducing non-content-based identifiers (access metrics) alongside traditional content-based identifiers. This dimensional expansion enables dynamic prioritization and real-time data management without replacing the existing content-based system, thus improving adaptability while managing complexity through layered architecture.
2Measurement precision
If the system tracks multiple access metrics dynamically, then data access control accuracy improves, but processing time and system response time worsen
Solution Approach 1:
Access metrics are characterized and stored in advance as non-content-based identifiers associated with data elements. This preliminary characterization allows the system to retrieve and process access control information quickly during operations, improving accuracy without significant time penalty since the heavy lifting of metric collection and analysis is performed beforehand.
Solution Approach 2:
The system introduces an intermediary layer of non-content-based identifiers that mediates between raw access data and decision-making processes. This intermediary structure pre-processes and organizes access metric information, enabling accurate data access control while reducing real-time processing requirements through efficient information retrieval and presentation.
3Productivity
If the system searches through all data elements to identify data of interest, then search completeness improves, but search efficiency deteriorates
Solution Approach 1:
The system extracts and isolates non-content-based identifiers (access metrics) as separate characterizing attributes from the main data element content. By taking out these identifiers, the system can efficiently search and filter data based on access metrics without processing entire data contents, thus improving identification efficiency while maintaining completeness through the comprehensive nature of access metric tracking.
Solution Approach 2:
Instead of analyzing all data element contents thoroughly, the system performs partial action by focusing search and identification operations on the non-content-based identifiers (access metrics) that characterize data of interest. This partial approach to data analysis significantly improves processing efficiency while the access metric framework ensures no relevant data is missed, as all data elements are characterized by these identifiers.
Data Source
AI summary
A method for managing data in an enterprise by identifying data of interest from among a multiplicity of data elements in an enterprise, the method including characterizing data of interest at least by at least one non-content based data identifier thereof and at least one access metric thereof, the at least one access metric being selected from data access permissions and actual data access history and selecting data of interest by considering only data elements from among the multiplicity of data elements which have the at least one non-content based data identifier thereof and the at least one access metric thereof.