Template Recommendation for Cross-System Data Exploration Automation
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Solution Overview
Problem
Organizations face inefficiencies and reduced productivity due to disparate systems lacking data analysis and visualization capabilities, making it difficult to correlate and analyze data across multiple disconnected systems.
Innovation Solution
A platform and method for recommending visual and execution templates that automate control and data exploration across multiple systems by establishing connections, rendering explorations based on user inputs, identifying target systems, and discovering best-fit templates for data visualization and control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually switch applications to view information across multiple disparate systems, then they can access data from different systems, but productivity decreases and efficiency is reduced
Solution Approach 1:
The patent merges multiple disparate systems into a unified interface where data from different sources (legacy systems, databases, external systems) can be viewed and analyzed in a single exploration workspace. This eliminates the need for users to switch between multiple applications while maintaining access to all required data sources.
Solution Approach 2:
The platform provides a universal interface that can connect to and operate with multiple different types of systems (legacy systems, databases, external systems) through a single application. This multi-functional capability allows users to access diverse data sources without needing separate applications for each system.
2Adaptability or versatility
If legacy systems are used without data analysis and exploration capabilities, then system compatibility is maintained, but data visualization and analysis become difficult
Solution Approach 1:
The patent introduces an intermediary platform that sits between legacy systems and users. This platform provides data analysis and visualization capabilities while the legacy systems themselves remain unchanged. The intermediary handles data extraction, transformation, and presentation, making it easy to analyze data from systems that lack native analysis capabilities.
3Loss of time
If data is extracted manually from databases associated with legacy systems, then data can be obtained, but the process becomes tedious and time-consuming
Solution Approach 1:
The platform enables self-service data extraction and exploration. Users can define explorations and data sources through configuration rather than manual extraction processes. The system automatically connects to databases, extracts required data, and makes it available for analysis, eliminating tedious manual operations.
4Loss of information
If data from multiple disconnected systems is captured separately, then each system operates independently, but correlating and analyzing data across systems becomes very difficult
Solution Approach 1:
The patent merges data from multiple disconnected systems into a unified data model within the platform. Data sources from different systems are connected and correlated through the platform's data layer, enabling users to perform cross-system analysis and draw insights that would be difficult to obtain from individual systems in isolation.
Data Source
AI summary
The present disclosure relates to platform configured to recommend Visual and Execution templates to automate exploration across one or more disparate systems. The platform is configured for receiving data from a target system. Further, the platform is configured to identifying a set of best fit templates, from a set of templates. In one embodiment, the set of templates may comprise one or more templates created by the user, one or more templates published by other users associated with the user, and one or more system generated templates. The platform is configured to analyze the set of templates based on the type of data received from the target system and a set of predefined rules to identify a subset of best fit templates (discovered Templates) from the set of templates. Furthermore, the platform is configured to execute the subset of best fit templates for performing one or more data processing operations.