Intent-Encoded Data Transform Repository
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Solution Overview
Problem
Developers across different units within an entity often redundantly create similar data transforms for different datasets, leading to inefficiencies in resource usage and storage, as existing systems do not effectively communicate or share transform intentions and similarities.
Innovation Solution
A system that encodes data transforms based on intent, allowing for the identification, recommendation, and combination of similar transforms across different units by associating transforms with data profiles based on characteristics and intent identifiers, reducing redundancy and improving resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If developers create data transforms independently in different units, then each unit can process its specific data requirements, but redundant transforms are created leading to resource waste and storage inefficiency
Solution Approach 1:
The patent merges similar transforms from different units by encoding them with intent identifiers and comparing characteristics. When similarity is detected, transforms are consolidated into a shared repository, eliminating redundant computational resources while maintaining the ability to serve multiple units' data processing needs.
Solution Approach 2:
The patent creates universal transforms that can serve multiple units and purposes by encoding transforms with intent identifiers that describe their functionality. A single transform can be reused across different units for similar data processing tasks, making the transform system multi-functional and reducing overall resource consumption.
2Ease of operation
If transforms are stored independently in each unit, then each unit has access to its specific transforms, but storage space is wasted and transform discovery becomes difficult
Solution Approach 1:
The patent combines transforms from multiple units into a centralized repository, storing each transform once with its intent identifier and characteristics. This merging eliminates duplicate storage across units while maintaining accessibility through the shared repository and recommendation system.
Solution Approach 2:
The patent introduces a transform repository and recommendation system as an intermediary between units and transforms. This intermediary centralizes storage to reduce space requirements while providing efficient access mechanisms that allow units to discover and retrieve appropriate transforms based on their needs.
3Ease of manufacture
If similar transforms are not identified across units, then each unit develops its own solutions, but this leads to redundant development effort and missed optimization opportunities
Solution Approach 1:
The patent implements feedback mechanisms where transform usage, success, and characteristics are tracked and fed back into the repository. This feedback loop allows the system to learn from actual transform performance and intent, improving recommendation accuracy and enabling identification of similar transforms across units based on real-world effectiveness.
Solution Approach 2:
The patent uses the transform repository and recommendation system as an intermediary that captures and shares transform intent information across units. This intermediary preserves intent data through encoding and characteristics, allowing units to discover similar transforms and avoid redundant development while maintaining awareness of what works best for specific data types.
Data Source
AI summary
The present disclosure provides systems for encoding transforms based on intent to be useable by developers. The system receives input datasets, generates output datasets, and identifies characteristics of the input or output datasets. Using these characteristics, the system can encode transforms associated with the datasets based on intent. The system stores and/or associates the intent-encoded transforms in data profiles, so that the system enables the transforms to be searched, recommended, and/or combined.