Dynamic Data Retention Management via Activity Windows
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Solution Overview
Problem
Organizations face escalating storage costs and resource consumption due to unchecked data copies, which can vary in importance over time, necessitating improved systems for calculating final data retention dates to manage data growth efficiently.
Innovation Solution
A system and method for calculating final data retention dates based on activity windows, where 'allowable activity windows' specify time periods when data artifacts should remain, allowing for selective retention and deletion of copies based on their creation context, such as time of day, day of week, or month, to optimize resource management and reduce storage burdens.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data copies are retained for longer periods to ensure data availability and compliance, then data reliability and security are improved, but storage costs and resource consumption increase
Solution Approach 1:
The patent implements dynamic retention periods that automatically adjust based on copy activity patterns. The system transitions from static, uniform retention policies to dynamic, context-aware retention management. Copies that remain inactive beyond defined activity windows are automatically deleted, while actively used copies are retained. This resolves the contradiction by making retention duration flexible rather than fixed, ensuring data availability when needed while eliminating unnecessary long-term storage of inactive copies.
Solution Approach 2:
The system performs preliminary analysis of copy creation contexts and usage patterns to pre-determine appropriate retention periods. By evaluating activity windows, copy purposes, and usage patterns at the time of creation or during periodic reviews, the system proactively sets retention policies before storage costs accumulate. This prevents both premature deletion of needed data and excessive retention of unnecessary copies, optimizing the balance between reliability and storage efficiency.
2Ease of operation
If uniform retention policies are applied to all data copies, then policy simplicity and ease of management are improved, but resource efficiency and storage optimization deteriorate
Solution Approach 1:
The patent applies different retention policies to different data copies based on their specific characteristics, usage patterns, and activity contexts. Instead of a blanket uniform policy, the system evaluates each copy individually against defined activity windows and retention criteria. This allows the organization to maintain simple, rule-based policy definitions while achieving differentiated, optimized retention outcomes for individual copies, thus improving resource efficiency without significantly complicating policy management.
Solution Approach 2:
The system enables automatic, self-managing retention policy enforcement through defined activity windows and automated deletion triggers. Once retention rules and activity window parameters are configured, the system autonomously evaluates copies, determines appropriate retention periods, and executes deletions without requiring continuous manual intervention. This maintains ease of operation by automating the complex decision-making process while achieving fine-grained, resource-efficient retention management.
3Measurement precision
If manual review processes are used to determine data retention dates, then retention accuracy and compliance are improved, but processing time and operational complexity increase
Solution Approach 1:
The patent replaces manual review processes with automated computational systems that apply defined activity window rules and retention criteria. The system automatically calculates retention dates based on copy creation timestamps, activity patterns, and predefined policy parameters, eliminating the need for human reviewers to manually assess each copy. This substitution maintains high retention date accuracy through consistent rule application while dramatically reducing processing time and operational complexity by automating the evaluation and decision-making process.
Solution Approach 2:
The system implements automated feedback loops that continuously monitor copy activity patterns and adjust retention decisions accordingly. By systematically tracking usage patterns, access timestamps, and activity windows, the system automatically refines retention date calculations without requiring manual intervention. This feedback-driven approach ensures accurate, compliance-appropriate retention decisions are made efficiently through automated analysis rather than time-consuming manual reviews.
Data Source
AI summary
Definitions are received for allowable activity windows and epochs. Each epoch specifies a retention duration and allowable activity window. There can be a retention policy specifying that copies created during a particular time period of the allowable activity window are to be retained past a retention duration of an initial epoch. A determination is made as to whether a copy was created during the particular time period specified in the retention policy. If the copy was not created during the particular time period, the retention duration of the initial epoch is added to a creation time of the copy to obtain a date after which the copy should be deleted. If the copy was created during the particular time period, a retention duration of a subsequent epoch is added to the creation time to obtain the date. The date is then associated with the copy.