Database Framework Transformer for Automated Data Extraction
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Solution Overview
Problem
Database systems require complex coding for data transformation and analysis, making it difficult for non-experts to access and manipulate large datasets, and existing solutions are inefficient in handling diverse data types and transformations.
Innovation Solution
The Database, Data Structure, and Framework Transformer (DDSFT) system allows non-database experts to transform and analyze data through a user-friendly interface, using orthogonal transformation mechanics, flag components, and automated data extraction, enabling the selection of variables, transformations, and data aggregation without writing custom code.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If complex coding is used for data transformation and analysis, then data processing capability is improved, but ease of operation deteriorates
Solution Approach 1:
The patent introduces an intermediary layer (the transformation system with predefined templates and automated code generation) between the user and the complex database operations. This intermediary handles the complexity of data transformation while presenting a simplified interface to users, resolving the contradiction between processing capability and ease of operation
Solution Approach 2:
The system enables self-service through automated code generation and template-based transformations. The system automatically generates the necessary coding and transformation logic based on user selections, eliminating the need for users to manually write complex code while maintaining high data processing capability
2Manufacturing precision
If custom coding is required for data transformation, then transformation precision is improved, but device complexity deteriorates
Solution Approach 1:
The patent segments the data transformation process into standardized, modular components (predefined templates, transformation types, and parameter sets). This segmentation allows for precise transformations through composition of standardized elements rather than custom coding, reducing overall system complexity while maintaining transformation precision
Solution Approach 2:
The system uses parameter changes to achieve different transformation outcomes. By modifying parameters within predefined transformation templates rather than changing the transformation logic itself, the system maintains precision while avoiding the complexity of custom coding for each transformation scenario
3Ease of operation
If existing transformation solutions are used, then ease of operation is improved, but adaptability deteriorates
Solution Approach 1:
The patent creates a universal transformation system with predefined templates that can handle multiple data types and transformation scenarios. This multi-functional approach allows the same system to adapt to different transformation needs while maintaining ease of operation through consistent interface patterns, resolving the contradiction between ease of use and adaptability
Data Source
AI summary
The Database, Data Structure and Framework Transformer Apparatuses, Methods and Systems (“DDSFT”) transforms variable list request, population selection, base table transform extract data inputs via DDSFT components into transformed, merged data outputs. The DDSFT includes a database structure that stores data used in the framework operations. A macro-tool includes one or more macros that control a sequence of database queries that extract the data from the database structure and then perform transformations on the extracted data. The macro-tool includes a series of binary flags indicative of whether or not statements are executed.