Anonymized Analytics for Automatic Data Protection Role Assignment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data backup systems require significant manual effort and time for initial configuration of backup/recovery systems, especially in newly deployed or reconfigured environments, due to the need for creating and fine-tuning backup policies that adhere to industry-specific guidelines, which is inefficient and resource-intensive.
Innovation Solution
A system that leverages asset metadata and anonymized analytics to automatically assign data protection policies by clustering assets based on common characteristics, using anonymized data from existing systems to quickly configure backup/recovery environments, reducing manual intervention and optimizing policy assignments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual assignment of backup policies is used, then policy accuracy and compliance can be ensured, but significant time and administrative effort are required for initial configuration
Solution Approach 1:
The system performs preliminary actions by automatically discovering assets, classifying them based on metadata, and pre-assigning appropriate backup policies before users need to configure anything. This eliminates the time-consuming manual configuration process while maintaining policy accuracy through automated classification algorithms.
Solution Approach 2:
The system enables self-service by allowing assets to be automatically classified and assigned to policies based on their own metadata characteristics. The automated policy assignment system serves itself by continuously monitoring asset changes and dynamically adjusting policy assignments without requiring administrator intervention.
2Productivity
If rule-based automatic assignment is used, then configuration time is reduced, but flexibility and adaptability to changing environments are limited
Solution Approach 1:
The system implements dynamic policy assignment that automatically adapts to changing environments. When assets are added, removed, or modified, the system dynamically recalculates policy assignments based on current asset metadata and business rules, ensuring continuous adaptability without requiring manual rule updates.
Solution Approach 2:
The system incorporates feedback mechanisms where policy assignment results are continuously monitored and used to refine future assignments. The system learns from assignment outcomes and asset changes, adjusting its classification and assignment logic to improve both speed and adaptability over time.
3Reliability
If comprehensive policy coverage is implemented, then data protection reliability is improved, but system complexity and administrative overhead increase
Solution Approach 1:
The system segments the complex policy management task into automated discovery, classification, and assignment components. By breaking down the overall policy coverage requirement into manageable automated steps, the system achieves comprehensive protection without increasing administrative complexity.
Solution Approach 2:
The automated policy assignment system acts as an intermediary between assets and backup policies. This intermediary automatically matches assets with appropriate policies based on metadata analysis, eliminating the need for administrators to directly manage complex policy configurations while ensuring comprehensive coverage.
Data Source
AI summary
Selecting user access policies for a new system, by collecting user, access policy, and resource metadata for a plurality of other users storing data dictated by one or more access restriction policies. The collected metadata is anonymized with respect to personal identifying information, and is stored in an anonymized analytics database. The system receives specific user, access policy and resource metadata for the new system from a specific user, and matches the received specific user metadata to the collected metadata to identify an optimum access policy of the one or more access policies based on the assets and access restriction requirements of the new system. The new system is then configured with the identified optimum access policy as an initial configuration.