Aggregate Banding Dimension for Data Segmentation
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Solution Overview
Problem
Current methods for analyzing data segments are complex, requiring technical expertise and specific setup, and are not data source or interface agnostic, making it difficult for end-users to create and reuse segmentation rules across different data sources and interfaces without administrative help.
Innovation Solution
The method involves defining an aggregate banding dimension with aggregation and banding variables, summarizing data, and creating a mapping relationship to enable easy analysis across different data sources and interfaces, allowing end-users to create and apply segmentation rules without technical knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional data segmentation methods are used, then analysis accuracy is maintained, but system complexity and difficulty of use increase significantly
Solution Approach 1:
The patent introduces an intermediary layer (the banding system with predefined bands and mapping relationships) between the raw data and the analysis process. This intermediary automatically handles the complex segmentation logic, allowing users to simply select bands without dealing with the underlying complexity of data segmentation algorithms and procedures
Solution Approach 2:
The system enables self-service by allowing users to automatically create and apply segmentation rules without requiring administrative assistance or technical expertise. The banding system provides self-contained tools that users can independently configure and execute, eliminating the need for external technical support
2Adaptability or versatility
If traditional data segmentation methods are used, then specific data source requirements are met, but adaptability across different data sources decreases
Solution Approach 1:
The banding system is designed with universal applicability across multiple data sources and types. The standardized band definitions and mapping mechanisms can be applied to any data source that can be summarized, making the system versatile and data source agnostic while maintaining reliable segmentation results across different contexts
3Productivity
If traditional data segmentation methods are used, then precise control is achieved, but ease of reuse and reproducibility decrease
Solution Approach 1:
The system performs preliminary actions by pre-defining bands and establishing mapping relationships before the actual analysis is needed. These pre-configured elements can be readily reused across multiple analyses and data sources, significantly improving productivity and reproducibility without sacrificing the ability to maintain precise control over segmentation criteria
Data Source
AI summary
The invention provides a method of aggregate banding comprising defining an aggregate banding dimension for a first data source, the aggregate banding dimension including at least one aggregation variable, at least one banding variable, and at least one band based at least partly on the at least one banding variable; summarizing the data source based at least partly on the at least one aggregation variable, the summary including at least one distinct value of the at least one aggregation variable; and defining a mapping relationship of the at least one distinct value of the at least one aggregation variable to the or respective band(s) based on the value of the at least one banding variable. The invention further provides related systems and processor-executable instructions.