Priority-Based Data Recovery for Faster Business Resumption
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Solution Overview
Problem
Existing data recovery techniques often result in critical data remaining inaccessible for an unnecessarily long time, impacting business operations due to a lack of prioritization based on business operations, and traditional recovery methods are resource and time-intensive, especially in large-scale data recovery scenarios.
Innovation Solution
A data recovery system that extracts insights on data usage and user access metrics to build relevance models, prioritizes recovery based on these insights, and restores critical data first, allowing the system to become operational quickly before completing the full recovery process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional sequential data recovery methods are used, then complete data recovery is achieved, but critical data remains inaccessible for an unnecessarily long time and business operations are impacted
Solution Approach 1:
The patent segments the data recovery process into priority-based groups. Data is classified into different priority levels (e.g., critical, important, standard) based on business impact analysis. The recovery system then processes and restores high-priority data first, allowing business operations to resume with essential data before completing the full recovery sequence. This segmentation resolves the contradiction by making critical data accessible sooner while ultimately achieving complete recovery.
Solution Approach 2:
The patent implements preliminary action by performing data classification and priority assignment before the actual recovery process begins. The system analyzes data metadata, business criticality, and operational dependencies in advance to create a recovery priority queue. This preliminary organization enables the system to immediately restore the most critical data when recovery is initiated, reducing the time critical data remains inaccessible while ensuring complete recovery is eventually achieved.
2Reliability
If traditional data recovery methods are used, then all data is recovered, but the process is resource and time-intensive especially in large-scale scenarios
Solution Approach 1:
The patent implements dynamic resource allocation and adaptive recovery sequencing. The system continuously monitors recovery progress, resource availability, and business operational status to adjust the recovery rate and priority assignments in real-time. High-priority data receives concentrated recovery resources initially, while lower-priority data recovery is paced according to available resources. This dynamic approach maximizes recovery speed for critical data without sacrificing ultimate completeness, resolving the contradiction between resource intensity and productivity.
3Device complexity
If no prioritization based on business operations is applied, then recovery process is simpler, but critical data remains inaccessible impacting business operations
Solution Approach 1:
The patent implements self-service by enabling the recovery system to automatically analyze data metadata, determine business criticality, and prioritize recovery without requiring manual intervention. The system uses embedded algorithms to assess data importance based on access patterns, file types, and business rules, then autonomously sequences the recovery process. This self-service capability adds minimal complexity while dramatically reducing critical data access time, as the system independently makes prioritization decisions without human involvement.
Data Source
AI summary
An application server may receive an input indicating a recovery priority for recovering data from a data backup environment to a data source environment and may receive data usage statistics indicating data access metrics and user access metrics corresponding to the data in the data source environment. The application server may generate, from the recovery priority and the data usage statistics, one or more data priority classifications for the data and may build a data model indicating an order for recovery of the data based on the one or more data priority classifications. The application server may then cause display of an indication of a progress of recovering the data from the data backup environment to the data source environment.