Data Quality Assessment System with Automated Workflow Triggering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data quality assessment technologies do not provide a comprehensive evaluation of enterprise data quality, lack flexibility in customization for different scenarios, and fail to automatically trigger workflow processes based on quality assessment results.
Innovation Solution
A system that integrates data quality metrics into enterprise data management processes using configuration rules, linking data quality assessment modules with a workflow engine to trigger processes and provide customizable assessments across various scenarios, including security considerations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If discrete technologies and algorithms are used for measuring data quality, then data quality measurement can be performed, but comprehensive assessment of all data quality aspects cannot be achieved
Solution Approach 1:
The patent combines multiple discrete data quality measurement technologies and algorithms into a single integrated system that simultaneously evaluates all aspects of data quality (completeness, accuracy, consistency, timeliness, accessibility) rather than measuring them separately
Solution Approach 2:
The system is designed to perform multiple data quality assessment functions through a unified framework that can measure various data quality dimensions and trigger different workflow processes based on comprehensive evaluation results
2Productivity
If fixed data quality assessment methods are used, then assessment can be performed, but flexibility for customization to user's data environment cannot be provided
Solution Approach 1:
The system employs dynamic configuration capabilities that allow assessment parameters, thresholds, and workflow rules to be customized and adjusted based on specific user requirements and data environments, making the rigid assessment process adaptable to varying scenarios
3Measurement precision
If data quality measurement results are not linked to triggering mechanisms, then measurement can be performed, but automatic workflow triggering based on quality assessment cannot be achieved
Solution Approach 1:
The system implements a feedback mechanism where data quality assessment results automatically trigger workflow processes based on pre-determined rules, creating a closed-loop system where measurement outcomes drive automated corrective or enhancement actions
Data Source
AI summary
A method and system for assessing data quality stored in an enterprise database is provided. In response to a request by a user, a pre-determined event, or other event, a profile is chosen from a list of profiles stored in a profile database based on the request, wherein the profile includes a set of rules for calculating data quality metrics and for triggering workflow processes. One or more data records are received from one or more enterprise databases. The data quality metrics of the one or more data records based on the set of rules for calculating data quality metrics is calculated. Based on the calculated data quality metrics and rules for triggering workflow, a determination is made regarding whether to trigger one or more workflow processes: and, if so, triggering the one or more workflow processes; and/or converting the calculated data quality metrics to a representation for display.