Spreadsheet-Like Data Transformation With Automatic Query Generation
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Solution Overview
Problem
Current data transformation methods, such as full-code approaches like Python or SQL, require significant expertise and are cumbersome, error-prone, and unintuitive, especially when dealing with complex schema mappings, making them inefficient for both technical and non-technical users.
Innovation Solution
A spreadsheet paradigm-based user interface that uses a no-code SQL approach, allowing users to interact with relational databases through familiar spreadsheet paradigms, automatically converting user inputs into executable database queries without the need for manual coding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If full-code methods (Python or SQL) are used for data transformation, then transformation power and flexibility are improved, but ease of operation deteriorates due to steep learning curve and requirement for highly skilled personnel
Solution Approach 1:
The patent introduces a visual mapping tool as an intermediary between the user and the database system. This tool provides a flow chart-like interface with drag-and-drop functionality, allowing users to create data transformations without writing code. The visual mappings are then translated into executable code by the system, bridging the gap between user-friendly interaction and powerful transformation capabilities.
Solution Approach 2:
The patent replaces the mechanical system of manual coding with an automated code generation system. Instead of users manually writing and debugging SQL or Python code, the system automatically generates the transformation code based on the visual mappings created by users through drag-and-drop operations, eliminating the need for programming expertise.
2Ease of operation
If visual mapping tools are used for data transformation, then ease of operation is improved, but device complexity worsens due to flow chart-like interface with multiple lines and annotated functions
Solution Approach 1:
The patent segments the complex transformation process into discrete, manageable mapping operations that can be performed through simple drag-and-drop actions. Each mapping operation is an independent unit that can be created, modified, and deleted separately, reducing the perceived complexity of the overall interface.
Solution Approach 2:
Instead of presenting users with a complex flow chart interface that requires understanding of multiple lines and annotated functions, the patent inverts the approach by providing a simple drag-and-drop interface that generates the complex mappings automatically. The complexity is hidden in the backend rather than being exposed to the user.
3Ease of operation
If mapping specifications are generated from visual tools and translated into executable code, then ease of operation is improved, but loss of time worsens due to the translation and deployment process
Solution Approach 1:
The system performs preliminary actions by pre-compiling and validating the mapping specifications as they are created by users. The translation into executable code and deployment to the runtime engine is done automatically and continuously, rather than requiring a separate manual step, thereby reducing the overall time required.
Solution Approach 2:
The patent implements continuous translation and deployment of mapping specifications. As users create or modify mappings in the visual interface, the system continuously translates these into executable code and updates the runtime engine, eliminating idle time and maintaining continuous productive action throughout the transformation process.
Data Source
AI summary
A system and method for data transformation using a spreadsheet paradigm-based user interface are disclosed. Data stored in a data table is processed and a subset of data is extracted. Spreadsheet-specific data processing options are displayed on a user interface along with the subset of the data, and a user is prompted to select one of the spreadsheet-specific data processing options. Subsequently, data processing actions corresponding to the user-selected spreadsheet-specific data processing options are identified. Subsequently, database queries are automatically generated for manipulating the subset of data, and the user-selected spreadsheet-specific data processing options and corresponding actions are programmatically transformed into database queries. The database queries, initially specific to the subset of data, are extrapolated to the entire data table, and corresponding spreadsheet-specific data processing options and actions are implemented on the entire data table, resulting in creation of transformed and updated data.