Information Retention Management via Segmented Storage and Dynamic Rules
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Solution Overview
Problem
Current information management systems lack efficient methods for determining retention periods and enforcing retention properties across multiple applications, leading to challenges in archiving and destroying business information in compliance with legal and business requirements.
Innovation Solution
The system determines retention periods and expiration dates based on information attributes, categorizes and indexes business objects, and transfers them to an archive, ensuring destruction upon expiration date, while allowing for modification of retention properties before and after archiving, and applying these rules to associated data and attachments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If information is retained in a primary system for extended periods, then data accessibility for review purposes is maintained, but storage costs increase and system efficiency decreases
Solution Approach 1:
The system segments information storage into two distinct environments: a primary system for actively used information and an archive system for retained information. This segmentation allows the primary system to maintain high performance and low storage costs while the archive system handles long-term retention, thus resolving the contradiction between data accessibility and storage costs.
Solution Approach 2:
The system introduces an information retention management application as an intermediary that automatically manages the transfer of information between the primary system and archive system based on retention properties. This intermediary handles the complexity of retention management, allowing the primary system to focus on core business operations while maintaining compliance with retention requirements.
2Reliability
If uniform retention rules are enforced across multiple applications, then compliance with legal and business requirements is improved, but device complexity increases
Solution Approach 1:
The information retention management application implements a universal retention framework that can be applied across multiple different business applications. By creating a single, reusable retention management system that works with various data types and applications, the solution improves compliance consistency while avoiding the complexity of implementing separate retention mechanisms for each application.
Solution Approach 2:
The system enables applications to self-manage their retention compliance by automatically applying retention rules to their data. The retention management application monitors and enforces retention properties without requiring manual intervention from each application, thus improving compliance while minimizing the operational complexity burden on individual applications.
3Productivity
If information is transferred to an archive system, then storage costs are reduced and primary system efficiency is improved, but data accessibility for modification is lost
Solution Approach 1:
The system implements dynamic retention properties that can change over time. Information can be transferred to the archive system when retention rules are satisfied, but the system maintains the flexibility to recall or modify archived information when business needs change. This dynamic approach allows the system to optimize for efficiency during retention periods while preserving the ability to modify data when necessary.
Data Source
AI summary
Methods, systems, and software for enforcing archival of data objects into archive objects and managed destruction of the archive objects are disclosed. In some cases, the computer techniques include enforcing a retention rule, such as a retention date and archive properties, and a destruction indication, such as an expiration date, of data identified for archival. The data objects are archived under hierarchical paths in a long-term storage system according to retention-related properties of the data objects and the retention rules. Further, the archived data can be destroyed according to destruction indications. Once archived, destruction of the data may be prevented by a hold applied to the data.