Automated Mass Data Quality Evaluation System
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Solution Overview
Problem
Current methods for automated data processing in technical processes lack automated evaluation of data quality, leading to manual and time-consuming comparisons, which are prone to errors and increase project costs and complexity.
Innovation Solution
A system and method for automated transfer and evaluation of mass data into a standardized environment, utilizing an assignment module for data mapping, a read-in module for automated data ingestion, a checking module for quality assessment, and a storage module for result logging, enabling automated quality evaluation and reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual comparison of mass data is performed, then data quality can be evaluated, but time requirement and expense increase proportionally to data quantity
Solution Approach 1:
The system performs automated self-checking of mass data quality through the checking module, which automatically evaluates completeness, consistency, validity, and other quality attributes without requiring manual user comparison. The system checks itself against predefined criteria and generates quality reports automatically.
Solution Approach 2:
The patent replaces the manual mechanical comparison process with an automated computer-based checking module that uses software algorithms to evaluate data quality. The checking module automatically reads data, compares it against criteria, and generates reports, substituting human manual comparison with automated computational processes.
2Measurement precision
If manual comparison of mass data is performed, then data quality can be evaluated, but expense increases proportionally to data quantity
Solution Approach 1:
The system performs automated self-checking of mass data quality through the checking module, which automatically evaluates completeness, consistency, validity, and other quality attributes without requiring manual user comparison. The system checks itself against predefined criteria and generates quality reports automatically.
Solution Approach 2:
The patent replaces the manual mechanical comparison process with an automated computer-based checking module that uses software algorithms to evaluate data quality. The checking module automatically reads data, compares it against criteria, and generates reports, substituting human manual comparison with automated computational processes.
3Measurement precision
If manual comparison of mass data is performed, then data quality can be evaluated, but errors occur and cannot be reproduced
Solution Approach 1:
The patent replaces the manual mechanical comparison process with an automated computer-based checking module that uses software algorithms to evaluate data quality. The checking module automatically reads data, compares it against criteria, and generates reports, substituting human manual comparison with automated computational processes.
Solution Approach 2:
The system provides automated feedback by generating quality reports that detail findings from the checking module. These reports include information about data quality issues, completeness problems, consistency errors, and other quality attributes, providing structured feedback that can be reproduced and reviewed consistently.
4Productivity
If mass data is read in automatically, then time is saved, but data quality evaluation is not performed
Solution Approach 1:
The checking module performs quality evaluation as a preliminary action immediately after data is read in, before the data is fully processed or stored. This allows the system to identify and report quality issues while the data is still accessible and can be corrected before further processing occurs.
Solution Approach 2:
The system maintains continuous operation by performing data reading, quality checking, and report generation in a continuous automated workflow. The checking module operates continuously alongside the data reading process, ensuring that quality evaluation is an ongoing function rather than a separate batch operation.
5Productivity
If mass data is read in automatically, then productivity is improved, but previously existing datasets can be overwritten without user planning
Solution Approach 1:
The quality report generated by the checking module provides feedback about the state of the mass data, including information about completeness, consistency, and validity. This feedback mechanism allows users to understand what data has been read in and its quality status before final processing, preventing unintended overwrites.
Solution Approach 2:
The checking module performs quality evaluation as a preliminary action immediately after data is read in, before the data is fully processed or stored. This allows the system to identify and report quality issues while the data is still accessible and can be corrected before further processing occurs.
Data Source
AI summary
The invention relates to a system and a method for automated transfer and subsequent evaluation of the quality of mass data of a technical process or a technical project in a standardized environment (70) of one or more data processing devices with an assignment module (20) for allocating the mass data from one or more data sources (10) to structure elements in the standardized environment of the data processing device (70) and for generating a defined mapping of the mass data to be read in. The assignment module (20) interacts with a read-in module (30), into which the mass data can be read in an automated operation according to the selected assignment. The data read in can be fed to a checking module (40) for automated checking and/or for generation of a report for evaluation of the quality of the measured data read in. The check results generated by the checking module (40) can be fed to a processing module (60) for automated logging in predefined structures, and the results of the check can be transferred into the standardized environment (70) of the data processing device.