Data Explorer Module for Real-Time Governance Policy Analysis
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Solution Overview
Problem
System administrators face challenges in managing data for hosted services due to the complexity of determining applicable policies and configurations across various regulatory, legal, and industry rules, especially in large-scale operations where manual management is impractical.
Innovation Solution
A data explorer module within a security and compliance service analyzes data, metadata, and activities to identify uncategorized data and determine applicable policies and remediation actions, using a correlated, multi-stage evaluated structure to provide real-time pivoting on data to model governance properties, thereby automating policy determination and implementation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual data management and policy determination is performed by system administrators, then policy implementation accuracy is improved, but administrative burden and time consumption increase significantly
Solution Approach 1:
The system enables self-service by automatically analyzing data, determining applicable policies, and generating remediation actions without requiring manual administrator intervention. The data explorer module autonomously evaluates data against governance rules and produces policy recommendations, freeing administrators from time-consuming manual analysis while maintaining accurate policy implementation.
Solution Approach 2:
The patent replaces the mechanical manual process of policy determination with an automated computational system. The data explorer module uses algorithmic analysis to evaluate data, classify it according to governance properties, and determine applicable policies, substituting human administrative work with automated information processing while preserving policy accuracy.
2Manufacturing precision
If comprehensive data analysis is performed to determine applicable policies, then compliance accuracy is improved, but processing capacity is consumed
Solution Approach 1:
The system performs preliminary action by pre-establishing governance rules, data classification schemes, and policy frameworks before actual data analysis occurs. The correlated multi-stage evaluated structure is prepared in advance, allowing the data explorer module to efficiently match data against pre-defined criteria rather than performing comprehensive analysis from scratch, thus reducing processing capacity consumption while maintaining compliance accuracy.
Solution Approach 2:
The patent segments the data analysis process into multiple evaluation stages with specific governance properties. The correlated multi-stage evaluated structure divides comprehensive analysis into discrete, manageable evaluation steps, each focusing on specific compliance criteria. This segmentation allows the system to determine applicable policies through incremental evaluation rather than consuming all processing capacity in a single comprehensive analysis pass.
3Speed
If real-time data analysis is implemented, then responsiveness to compliance issues is improved, but system complexity increases
Solution Approach 1:
The data explorer module is designed as a universal, multi-functional system that handles multiple governance properties and policy types through a single integrated platform. Rather than implementing separate complex systems for different compliance requirements, the module provides real-time analysis capabilities across diverse data types and governance scenarios, achieving responsiveness without proportionally increasing system complexity through consolidation and reusability.
4Ease of operation
If automated policy determination is implemented, then administrative burden is reduced, but measurement precision of data classification may worsen
Solution Approach 1:
The system implements feedback mechanisms where the automated policy determination process continuously evaluates data classification results and refines its analysis based on governance rules and policy requirements. The data explorer module provides feedback loops that verify classification accuracy and adjust automated determination algorithms, ensuring that reduced administrative burden does not compromise data classification precision.
Data Source
AI summary
Real time pivoting on data to model governance properties is provided. A data explorer module of a security and compliance service may analyze data, metadata, and activities associated with a tenant or a hosted service to understand the data, identify uncategorized data, and determine applicable policies and/or remediation actions in case of sensitive data that may need protection. The data may be stored and managed by a data insights platform which may enable query-based analyses on correlated, multi-stage evaluated data. Thus, the data may be analyzed, additionally, considering metadata, activities associated with the data, etc. In addition to the data, metadata, and activities, the data explorer module may receive information associated with existing classifications, properties, access, and applied policies. Upon evaluation of the data based on the received/stored factors, the data explores module may identify the data and determine applicable policies or actions.