Self-Management Engine for Automated Data Compliance
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Solution Overview
Problem
Manually monitoring and enforcing guidelines, standards, and best practices across software applications is expensive, time-consuming, and often results in costly issues due to the retroactive and unfocused nature of random checks, leading to potential system instability and unavailability, which can result in significant financial losses.
Innovation Solution
A self-management engine retrieves health data from data storage, detects patterns in data utilization, and automatically determines and applies corrections based on predefined rules to ensure compliance with guidelines, standards, and best practices, thereby maintaining system stability and availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual monitoring and enforcement of guidelines is implemented, then compliance with standards can be detected, but the cost and time consumption increase significantly
Solution Approach 1:
The system enables self-service automation where the self-management engine automatically monitors data applications, detects guideline violations, and applies corrections without human intervention. The engine retrieves health data, detects patterns indicating compliance issues, determines appropriate corrections based on predefined rules, and implements them automatically, making the system self-regulating and eliminating the need for manual monitoring.
Solution Approach 2:
The patent replaces the mechanical manual monitoring process with an automated electronic system. The self-management engine uses computer-based algorithms to analyze health data, detect compliance patterns, and apply corrections, substituting human administrators' manual efforts with an automated computational system that operates continuously without time constraints.
2Reliability
If random checks of data are performed to ensure adherence to standards, then some deviations can be identified, but many costly problems occur due to the retroactive and unfocused nature
Solution Approach 1:
The system implements continuous feedback monitoring by constantly retrieving health data from data applications and analyzing it against predefined guidelines and best practices. The self-management engine detects patterns in real-time, providing ongoing feedback about compliance status, and automatically applies corrections when deviations are detected, ensuring continuous adherence rather than retroactive detection.
Solution Approach 2:
The system performs preliminary actions by proactively monitoring health data and detecting potential compliance issues before they escalate into costly problems. The self-management engine continuously analyzes data patterns and applies corrections in advance, preventing deviations from becoming significant issues rather than reacting retroactively after problems occur.
3Productivity
If automated self-management is implemented, then continuous monitoring and correction can be performed, but system complexity increases
Solution Approach 1:
The self-management engine is designed as a universal multi-functional system that can monitor multiple data applications across different technologies and platforms. It retrieves health data from various sources, detects diverse compliance patterns, applies appropriate corrections based on predefined rules, and maintains system-wide adherence to guidelines, consolidating multiple monitoring functions into a single automated platform.
Data Source
AI summary
The present embodiments relate generally to the enforcement of guidelines, standards, and best practices for software applications. According to certain aspects, a method of retrieving, by a self-management engine from a data storage device, health data indicative of a utilization of a collection of data by one or more computing devices is disclosed, including detecting, by the self-management engine, a pattern in the utilization of the collection of data based on the health data; automatically determining, by the self-management engine, a correction to be applied to the collection of data based on the detected pattern and based on one or more rules corresponding to the detected pattern; and causing, by the self-management engine, the correction to be applied to the collection of data.