Data Transformation UI for Real-Time Schema Mapping
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Solution Overview
Problem
The complexity and cost of managing data flow across different systems, especially when format changes are required, is high due to the need for manual schema definition and code overhaul, making it time-intensive and error-prone.
Innovation Solution
A transformation platform providing 'transformation as a service' with a user interface that enables dynamic and flexible data transformation, allowing users to define target output formats, establish connections, and perform rule-based data injection and enrichment, facilitating real-time transformation of input data into desired formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual schema definition and code overhaul are used for data format changes, then data transformation can be achieved, but project complexity and time consumption increase significantly
Solution Approach 1:
The patent introduces a transformation platform as an intermediary component between data sources and target systems. This platform provides pre-built transformation templates and a visual configuration interface that mediates the data transformation process, eliminating the need for manual schema definition and code overhaul while maintaining adaptability to different data formats.
Solution Approach 2:
The system enables dynamic parameter changes through a visual interface where users can configure transformation parameters without modifying underlying code. The platform supports parameterized transformation templates that can be adapted to different data formats by simply changing configuration parameters rather than rewriting schemas or code.
2Adaptability or versatility
If manual schema definition and code overhaul are used for data format changes, then data transformation can be achieved, but development time and cost increase
Solution Approach 1:
The transformation platform provides pre-built transformation templates and pre-configured transformation logic that are prepared in advance. Users can select from these pre-prepared templates and simply configure specific parameters, eliminating the need to manually define schemas and write transformation code from scratch, thereby significantly reducing development time.
Solution Approach 2:
The platform enables self-service transformation through a visual configuration interface where users can independently define transformation rules and map data fields without requiring developer intervention. The system automatically generates transformation code based on user configurations, allowing business users to perform data format changes independently without time-consuming manual schema definition.
3Adaptability or versatility
If manual schema definition and code overhaul are used for data format changes, then data transformation can be achieved, but error rates increase
Solution Approach 1:
The transformation platform incorporates validation mechanisms that provide real-time feedback on transformation configurations. The system automatically validates mapping rules, data type conversions, and schema transformations, highlighting potential errors before execution. This feedback mechanism ensures transformation accuracy by catching errors early without requiring manual code review.
Solution Approach 2:
The patent replaces manual mechanical processes of schema definition and code writing with an automated visual configuration system. The platform substitutes manual coding operations with graphical interface-based configuration, where transformation rules are defined through visual drag-and-drop operations and parameter selection, eliminating human errors associated with manual coding while maintaining full adaptability to different data formats.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, receiving input data via a transformation UI, generating transformation configuration data, causing the transformation UI to present transformation object data per the transformation configuration data, where the transformation object data identifies data objects each including an input and output field name and a data type, detecting, from the transformation UI, an instruction defining a mapping for the input data, including a modification to the output field name of a data object such that the input field name of the data object is mapped to the modified output field name, based on the detecting the instruction, modifying the first transformation configuration data per the mapping to derive second transformation configuration data, performing a transformation of the input data based on the second transformation configuration data, and causing the transformation UI to present a transformation output. Other embodiments are disclosed.


