User Profile-Based Data Analytics Request Routing
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Solution Overview
Problem
Users with limited access to data analytics face challenges in identifying appropriate data sources and types of analysis, leading to inefficient and inaccurate data analysis results.
Innovation Solution
A computer-implemented method that creates a customized request based on a user's profile to map to a specific data-constrained analytic algorithm, performing the appropriate type of data analysis on the appropriate data source and transmitting the results to the user, while offering options for different analysis types and resources to optimize efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users with limited access to data analytics perform data analysis themselves, then they can access data analytics, but they cannot identify appropriate data sources and analysis types leading to inaccurate results
Solution Approach 1:
The system introduces an intermediary layer between users and data analytics resources. This intermediary automatically interprets user intent from preliminary requests, identifies appropriate data sources and analysis types, and maps requests to suitable algorithms. Users with limited expertise can thus access accurate data analytics through this mediating system without needing to understand the underlying complexity.
Solution Approach 2:
The system performs preliminary actions by pre-configuring mappings between user profiles, data sources, and analysis algorithms. Before users make requests, the system has already established the relationships and constraints needed to automatically route requests to appropriate resources. This preliminary setup enables users to make simple requests without needing to specify technical details.
2Measurement precision
If users specify detailed data sources and analysis types themselves, then accurate analysis results can be obtained, but the operation becomes complex and time-consuming
Solution Approach 1:
The system enables self-service by automatically performing the complex tasks of identifying data sources and selecting analysis types based on user profiles and preliminary requests. The system serves itself by having pre-established mappings and algorithms that automatically resolve the technical details without requiring user intervention. Users simply state their intent, and the system handles the rest autonomously.
Solution Approach 2:
The system creates a universal interface that handles multiple functions through a single simplified request mechanism. One preliminary request can trigger automatic identification of data sources, selection of analysis types, and execution of appropriate algorithms. This multi-functional approach allows users to obtain accurate results without navigating complex separate steps for each technical parameter.
3Productivity
If the system provides multiple options for analysis types and resources, then users can optimize efficiency, but the system complexity increases
Solution Approach 1:
The system segments the complex data analysis process into distinct manageable components: user profile storage, preliminary request interpretation, data source identification, analysis type selection, and algorithm execution. Each segment is handled by specialized modules that work together through standardized interfaces. This segmentation allows the system to provide multiple optimization options while maintaining manageable complexity through modular architecture.
Data Source
AI summary
A computer implemented method, system, and/or computer program product performs an appropriate type of data analysis for a user. A preliminary request for a data analysis is received from a user having a user profile. The preliminary request fails to identify an appropriate data source for the data analysis, and fails to identify an appropriate type of data analysis. Thus, a customized request, that identifies the appropriate data source for analysis, is created from the preliminary request based on the user's profile. The customized request is mapped, based on the user's profile, to a specific data constrained analytic algorithm that performs the appropriate type of data analysis. This specific data constrained analytic algorithm performs the appropriate type of data analysis on the appropriate data source in order to generate an analytic result, which is transmitted to the user.