Business Intelligence Tool Transaction Tracking for Personalized Suggestions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users of business intelligence tools face inefficiencies in data manipulation and visualization, as they need to repeatedly perform similar tasks, which can be time-consuming and labor-intensive, especially for users with different roles who require tailored data insights.
Innovation Solution
A computer-implemented method that tracks user actions and stores transaction information, allowing for the generation of personalized suggestions based on previous user interactions, enabling users to quickly access and apply relevant operations and parameters, thereby streamlining data preparation, visualization, and sharing processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually perform data manipulation and visualization tasks repeatedly, then they can access and process business data, but the time and effort required increases significantly
Solution Approach 1:
The system performs preliminary actions by automatically tracking and storing user actions and transaction information in advance. When similar tasks are detected, the system retrieves previously stored transaction information and applies it automatically, eliminating the need for users to manually repeat the same data manipulation and visualization steps
Solution Approach 2:
The system provides self-service functionality by automatically monitoring user actions, storing transaction information, and suggesting relevant operations without requiring user intervention. The system serves itself by managing the tracking, storage, and retrieval of transaction data, and by automatically applying suggested operations to reduce manual effort
2Adaptability or versatility
If the system provides comprehensive data access and manipulation capabilities, then users can perform detailed analysis, but the complexity of the interface and operations increases
Solution Approach 1:
The system implements feedback by monitoring user actions and using this information to generate personalized suggestions. The feedback loop tracks what operations users perform, stores this transaction information, and then uses it to suggest relevant operations for future tasks, adapting the interface to user behavior patterns and reducing the perceived complexity
Solution Approach 2:
The system applies local quality by providing context-specific suggestions tailored to individual users and their current needs. Rather than presenting all possible operations uniformly, the system selectively displays relevant suggestions based on monitored user actions and current transaction contexts, making the interface simpler for each user's specific situation
3Ease of operation
If the system tracks and stores detailed transaction information for all user actions, then personalized suggestions can be generated, but the data storage and processing requirements increase
Solution Approach 1:
The system extracts only the essential and relevant transaction information needed for generating suggestions, rather than storing all possible data. By selectively capturing key user actions and transaction parameters, the system reduces the volume of stored data while maintaining the capability to generate personalized suggestions
Data Source
AI summary
The disclosure generally describes computer-implemented methods, software, and systems, including a method for providing suggestions. Transaction information is received that is associated with user actions during use by a user of a business intelligence tool. Each user action is associated with an operation in a particular stage of processing on business data obtained from one or more databases. The transaction information for a particular user action includes a user identifier identifying the user performing the particular user action, stage information, an associated operation, and parameters. The transaction information is stored. Subsequent user actions are monitored, including determining a time at which stage conditions match stage information in the stored transaction information. In response to determining matching stage conditions, pertinent transactions are identified. Suggestions are created. Each suggestion is associated with groups of one or more transactions of the pertinent transactions. The suggestions are provided for presentation to the user.