Data Marketplace for Decision Application Discovery
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Solution Overview
Problem
Discovering and accessing relevant data sources for business intelligence applications is time-consuming and challenging, as developers must visit multiple websites, purchase data separately, and often cannot interact with data feeds until payment, lacking a trial run capability.
Innovation Solution
A crowd-sourcing solution for development, discovery, and publication of decision applications, where users can submit applications to a data warehouse with data feeds, determine discovery properties, and select relevant applications for evaluation and customization, with automated generation of preview applications and user feedback mechanisms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If data source companies provide directories of data feeds and display samples, then data discovery is enabled, but developers cannot interact with data feeds until payment, preventing trial runs
Solution Approach 1:
The system generates preview applications that allow developers to interact with data feeds before purchase. The data warehouse creates these preview applications automatically when developers submit discovery requests, enabling trial runs without requiring payment first. This preliminary action resolves the contradiction by providing interactive data access capability before the purchasing step.
Solution Approach 2:
The data warehouse acts as an intermediary between data source companies and developers. It receives discovery requests from developers, determines relevant data feeds, generates preview applications, and makes them available for interaction. This intermediary function enables developers to test data feeds without direct contact requirements from data source companies, resolving the interaction capability issue.
2Productivity
If data source companies create custom applications to attract subscribers, then data feed promotion is improved, but significant development effort is required
Solution Approach 1:
The data warehouse performs self-service by automatically generating preview applications based on data feed metadata and discovery requests. Instead of requiring data source companies to manually create custom applications, the system autonomously determines relevant applications and generates them, reducing development effort while maintaining effective promotion capability.
Solution Approach 2:
The system changes the parameters of application generation from manual customization to automated parameter-based generation. By analyzing data feed metadata and matching it with appropriate application templates, the system generates customized preview applications without requiring significant development effort from data source companies.
3Reliability
If developers visit multiple data source company websites to find relevant data, then data source identification is possible, but the process is time-consuming
Solution Approach 1:
The system implements feedback mechanisms where developers submit discovery requests describing their data needs. The data warehouse processes these requests, determines relevant data feeds, and provides targeted results. This feedback loop eliminates the need for developers to systematically visit multiple websites, reducing search time while maintaining identification accuracy.
Solution Approach 2:
The data warehouse serves multiple functions: it stores data feed information, processes discovery requests, determines relevant data feeds, generates preview applications, and facilitates interactions. This universal platform replaces the fragmented process of visiting multiple individual company websites, reducing time while maintaining comprehensive data source identification capability.
Data Source
AI summary
A data marketplace infrastructure provides a crowd sourcing solution to development, discovery and publication of decision applications. Applications can be submitted from a user to a data warehouse in association with a data feed. One or more discovery properties are determined with regard to each application. The applications are made available to other client systems in association with the data feed. A relevant data feed and a relevant application can be identified based on satisfaction of a discovery request by the one or more determined discovery properties of the application. The application can be selected and downloaded to the user for evaluation and customization. The customized application can then be submitted to the data warehouse for publication with the other applications associated with the data feed.