Real-Time Data Validation and Correction in Software Entry
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current commercial software for managing business events, such as meeting and event planning, lacks effective real-time data validation and correction mechanisms, leading to inaccurate data entry and time-consuming error correction processes, which hinder efficient decision-making and increase labor costs.
Innovation Solution
A non-transitory computer-readable medium with computer-executable instructions that provides real-time data validation and correction by flagging errors, offering suggestions, and using machine learning to complete missing fields, allowing users to correct data in real-time through a graphical user interface within the existing software.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual data review and correction processes are used, then data accuracy can be improved, but labor costs and time consumption increase significantly
Solution Approach 1:
The system performs self-validation of data entries by automatically checking entered data against predefined business rules, validation schemas, and cross-field dependencies. The software identifies errors, missing information, and inconsistencies without requiring manual review, thereby maintaining data accuracy while eliminating the time-consuming manual correction process.
Solution Approach 2:
The system provides immediate feedback to users when data entry errors are detected, displaying specific validation messages that guide users to correct the issues. This real-time feedback mechanism ensures data accuracy is maintained while preventing time loss through post-entry review, as errors are identified and corrected at the point of entry.
2Productivity
If semi-automated data validation rules are implemented, then processing speed improves, but system complexity and implementation costs increase
Solution Approach 1:
The system incorporates validation rules, data schemas, and business logic constraints directly into the data entry interface before users submit data. This preliminary validation action prevents invalid data from being entered in the first place, improving processing speed by eliminating the need for post-entry validation while keeping the system relatively simple through standardized validation frameworks.
Solution Approach 2:
The validation system uses universal, reusable validation schemas and business rules that can be applied across multiple data fields and entry points. This multi-functional approach allows the same validation infrastructure to handle various data types and validation scenarios, improving processing speed without proportionally increasing system complexity.
3Reliability
If comprehensive field validation is implemented, then data quality improves, but user interface complexity and ease of operation deteriorate
Solution Approach 1:
The system applies validation rules and error checking specifically at the local level of individual data fields and their interrelationships, rather than requiring users to navigate complex global validation systems. Validation messages and corrections are presented contextually at the point of error, maintaining data quality while preserving user interface simplicity through localized, intuitive feedback.
4Measurement precision
If real-time error detection and correction is provided, then data accuracy improves, but computational resources and processing time increase
Solution Approach 1:
The system performs partial validation by checking only the specific data fields and relationships that are relevant to the current entry context, rather than validating the entire dataset simultaneously. This selective validation approach maintains high data accuracy for entered fields while reducing unnecessary computational overhead by avoiding redundant checks across all system data.
Data Source
AI summary
A guidance system and method to supplement the functionality of software programs in a manner that is not native to a target software to guide and enable a user to provide more complete and correct information in real time and hence have better information available at a lower cost. The system provides onscreen, real time guidance, reports and suggested answers for data entry, and actions at particular points in the user's workflow within a primary system. The guidance system may present data in a predetermined format based on algorithms which consider aspects of the user and the users previous actions, the location of the user in the target system, the context of other data inside and external to the target system, and ongoing artificial intelligence of the guidance system.