Extensible Data Transformation Programs From Example Values
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Solution Overview
Problem
Data transformation processes are often difficult and time-consuming due to the need for manual search and application of different transformation operations for diverse data formats, leading to inefficiencies in converting data to a consistent format for analysis.
Innovation Solution
A transformation engine dynamically generates transformation programs based on example input and output values, searching a collection of tools to identify relevant functions, tables, and services, and ranks them for suggested data transformations, using supplemental tools if necessary to achieve the desired format.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual search and development of transformation operations is performed, then transformation accuracy can be controlled, but transformation time and operational complexity increase significantly
Solution Approach 1:
The system performs self-service by automatically generating transformation operations based on detected data formats. The transformation engine analyzes input data, identifies appropriate transformation functions from a repository, and constructs transformation programs without requiring manual user development, thereby reducing time while maintaining accuracy through automated intelligent generation
Solution Approach 2:
The system performs preliminary action by pre-building a comprehensive repository of transformation functions and pre-defining transformation patterns. When transformation is needed, the engine searches this pre-organized knowledge base and selects appropriate functions, avoiding the need for manual search and development while ensuring accurate transformations
2Adaptability or versatility
If multiple transformation operations are applied to handle diverse data formats, then data format versatility is improved, but operational complexity and difficulty increase
Solution Approach 1:
The system implements universality through a centralized transformation engine that handles multiple data format conversions using a unified approach. The engine maintains a comprehensive repository of transformation functions that can be selectively applied to different data types, providing versatile format conversion capability while keeping the user interface simple and the overall system complexity managed through automation
Solution Approach 2:
The system applies segmentation by dividing the transformation process into discrete, manageable functions stored in the repository. Each transformation operation is segmented as a separate function that can be independently selected and combined, allowing the system to handle diverse formats through modular function composition rather than monolithic complex operations
3Reliability
If transformation operations are manually developed for each data format, then specific transformation requirements can be met, but productivity and efficiency decrease
Solution Approach 1:
The transformation engine performs self-service by automatically analyzing data formats, selecting appropriate transformation functions from the repository, and generating transformation programs without manual intervention. This automated self-service approach maintains reliable fulfillment of transformation requirements through intelligent function selection while dramatically improving productivity by eliminating manual development time
Solution Approach 2:
The system implements feedback mechanisms where the transformation engine analyzes the input data, evaluates transformation results, and adjusts function selection accordingly. This feedback loop ensures that transformation requirements are reliably met by continuously optimizing the selected transformation functions while maintaining high efficiency through automated iterative improvement
Data Source
AI summary
Methods, computer systems, computer-storage media, and graphical user interfaces are provided for facilitating data transformations, according to embodiments of the present invention. In one embodiment, a set of example values are received. A repository of transformation tools is searched to identify a new transformation tool as relevant to a data transformation associated with the received set of example values. The repository includes annotations associated with the new transformation tool. The new transformation tool is used to generate a transformation program that produces transformed output values. Additional annotations are generated for the new transformation tool based on the transformed output values.