Data Transformation UI for Real-Time Field Mapping and Output Preview
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Solution Overview
Problem
Managing data flow across different systems is challenging due to the complexity of data communications, requiring manual processes that are time-intensive, costly, and error-prone, especially when data format changes are needed.
Innovation Solution
A transformation platform providing 'transformation as a service' with a user interface that enables real-time or near real-time data transformation, allowing users to define target output formats, establish communication connections, and perform rule-based data injection and enrichment, including the creation of virtual fields.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data transformation processes are used, then data can be transformed between different formats, but the process becomes time-intensive and error-prone
Solution Approach 1:
The system enables self-service data transformation through a user interface where users can configure transformation parameters, select data sources, and define target formats without requiring manual coding or complex configuration. The platform automatically executes transformations based on user-defined rules, eliminating the need for manual intervention in the transformation process itself.
Solution Approach 2:
The system allows dynamic change of transformation parameters such as data formats, field mappings, and validation rules through the user interface. Users can modify these parameters in real-time without reconfiguring the entire transformation pipeline, enabling flexible adaptation to different data requirements while maintaining automated execution.
2Adaptability or versatility
If manual schema definition and code development are used for data flow, then data can be transformed between systems, but the process becomes costly and complex
Solution Approach 1:
The system introduces a transformation platform as an intermediary layer between different data systems. This platform provides standardized interfaces and pre-defined transformation templates that simplify the connection between source and target systems, eliminating the need for custom integration code while maintaining the ability to handle diverse data formats.
Solution Approach 2:
The transformation platform serves multiple functions including data transformation, validation, enrichment, and format conversion within a single unified system. Users can leverage pre-built templates and reusable components to handle various data scenarios without developing separate solutions for each requirement, reducing overall system complexity.
3Productivity
If existing transformation tools are used, then data transformation can be performed, but real-time configuration and visualization capabilities are limited
Solution Approach 1:
The system incorporates real-time feedback mechanisms that allow users to visualize transformation outputs as they are processed. The user interface provides immediate feedback on transformation status, success rates, and sample outputs, enabling users to monitor and adjust transformations in real-time without disrupting the overall processing flow.
Solution Approach 2:
The platform allows users to pre-configure transformation parameters, validate data samples, and preview transformation results before executing full-scale transformations. This preliminary configuration and visualization capability enables users to verify correctness and optimize performance settings ahead of time, ensuring smooth real-time execution.
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.