Data Type Identifier Changing Application for Table Columns
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Solution Overview
Problem
Data type mismatches occur in columns of tables due to incorrect user input, leading to data quality issues and operational inconsistencies, as existing technologies lack effective mechanisms for correcting and managing diverse data types within a single column.
Innovation Solution
A system and method that allows users to select a column, generate a list of data type identifiers, change the type of selected rows to match another identifier within the list, or change to a new type not initially present, ensuring only one data type is associated with the column, using a user interface that displays row counts and allows iterative corrections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users manually correct data type identifiers in each row, then data type consistency is improved, but time consumption and operational complexity increase significantly
Solution Approach 1:
The system segments the data correction task by identifying groups of rows with the same data type identifier mismatches and allowing users to select and correct multiple rows simultaneously. Instead of correcting each row individually, the system divides the work into manageable groups that can be processed together, significantly reducing the time required while maintaining data type consistency across all rows.
Solution Approach 2:
The system introduces an intermediary mechanism that automatically detects data type identifier mismatches and presents them to users for review. This intermediary layer acts as a bridge between the raw data and the user, pre-processing the data to identify issues and organize them for efficient correction, thereby reducing the manual effort required while ensuring accurate corrections.
2Reliability
If users manually review and correct each data entry, then data quality is improved, but productivity decreases due to repetitive manual work
Solution Approach 1:
The system performs preliminary actions by automatically scanning and identifying all data type identifier mismatches before user intervention is required. It pre-processes the data to organize mismatches by column and row, and prepares correction options in advance. This preliminary detection and organization significantly reduces the time users need to spend on each correction while maintaining high data quality standards through systematic review.
Solution Approach 2:
The system enables self-service by allowing users to select multiple rows with mismatched data type identifiers and apply corrections to entire groups at once. Instead of requiring users to manually review and correct each entry individually, the system empowers users to perform bulk corrections while maintaining quality control through the ability to review changes before final application, thereby dramatically improving operational efficiency.
3Measurement precision
If the system provides detailed lists of all data type identifiers in a column, then data type identification accuracy is improved, but information overload and user confusion increase
Solution Approach 1:
The system applies local quality by providing detailed data type identifier information only where needed - specifically in the context of identified mismatches. Instead of displaying all possible data type identifiers globally, the system focuses on showing relevant identifiers for the specific column and row being examined, reducing information overload while maintaining identification accuracy through context-specific detail.
Solution Approach 2:
The system segments the information display by organizing data type identifier details according to specific columns and mismatched rows. Rather than presenting a single comprehensive list of all data types in the entire dataset, the system divides the information into column-specific segments and row-specific mismatch details, making the interface less complex while maintaining precision in identifying and correcting data type issues.
Data Source
AI summary
A system includes an operating system executed by a processor and memory. A data type identifier changing application is executed by the operating system and is configured to display a table including data entries that are arranged in rows and columns and that include data type identifiers. The data type identifier changing application is configured to generate a list including two or more of the data type identifiers corresponding to rows in a selected column. The data type identifier changing application is configured to change one of the data type identifiers in the list corresponding to a plurality of rows in the selected column to one of another one of the data type identifiers in the list or a data type identifier that is not in the list.