Reusable Data Transformation Engine for Incompatible Type Mapping
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Solution Overview
Problem
Existing methods for converting data between incompatible types, such as XML, are complex and error-prone, requiring technical expertise and often result in inefficient data transformations.
Innovation Solution
A data transformation engine that allows users to specify mappings between data types in a reusable fashion, analyzing input and output data to determine potential mappings and generating transformation files for execution, including the use of nodal analysis and placeholder nodes to ensure accurate and efficient data conversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If XSLT files are used for data transformation, then data can be converted between incompatible types, but the process becomes extremely technical and error-prone
Solution Approach 1:
The patent introduces an intermediary data mapping tool that sits between the source and target systems, automatically generating transformation logic based on user-defined mappings. This intermediary layer handles the complex XSLT generation and execution, shielding users from technical complexity while maintaining adaptability between incompatible data types.
Solution Approach 2:
The system enables self-service data transformation by allowing users to define simple mapping rules between data types without requiring expertise in XSLT or transformation languages. The tool automatically handles the complex transformation logic generation and execution, making the process accessible to non-technical users.
2Reliability
If custom XSLT files are written for each transformation, then specific data type conversions can be achieved, but the process is time-consuming and requires extensive technical knowledge
Solution Approach 1:
The patent implements preliminary action by pre-defining common data type mappings and transformation templates that can be reused across multiple transformations. Users can select from pre-configured mapping patterns rather than writing custom XSLT from scratch, significantly reducing setup time while maintaining transformation accuracy through proven mapping templates.
Solution Approach 2:
The system enables copying of proven transformation mappings between different data type pairs. Once a mapping is defined and validated for one transformation, it can be copied and reused for similar transformations, reducing both time investment and technical complexity while ensuring consistent, reliable transformation logic across multiple use cases.
3Ease of operation
If manual mapping definitions are created for each data transformation, then precise control over transformation logic is achieved, but the process lacks reusability and scalability
Solution Approach 1:
The patent implements universality by creating a reusable mapping framework where transformation logic defined once can be applied to multiple data transformation scenarios. The system supports parameterized mappings that can adapt to different source and target data types while maintaining the same transformation logic, significantly improving productivity without sacrificing mapping control.
Data Source
AI summary
In one implementation, a data transformation tool is configured to allow a user to specify how types of data should be mapped to another type of data in a reusable fashion. In one implementation, the data transformation tool analyzes data selected for input, the desired data output, and determines a list of potential mappings that may be used between the compliant and non-compliant systems. The mappings may be generated through transformational expressions and defined as a data wrapper. Once the definition of the one or more mappings are defined, data transformation tool generates one or more files allowing the execution of the transformation of the input data to the output data during an execution phase, such as runtime.