Trading Partner Manager Data Fabric Configuration
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Solution Overview
Problem
Current big data platforms require significant human and capital resources for managing and utilizing vast amounts of data, often necessitating database management expertise, limiting user autonomy in implementing changes or extracting specific data arrangements.
Innovation Solution
A Data Management as a Service platform utilizing a trading partner management interface allows users to independently manage and consume data through predefined data fabric configurations, automating database management processes and reducing resource redundancy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional database management approaches are used, then data can be managed and processed, but significant human resources and database management expertise are required, limiting user autonomy
Solution Approach 1:
The patent implements self-service by allowing users to independently configure data ingestion, enrichment, and consumption through a user-friendly interface. Users can define data fabric configurations without requiring database administrator intervention, enabling them to autonomously manage their own data needs while the system handles the complex underlying database operations automatically.
Solution Approach 2:
The patent introduces a Trading Partner Manager (TPM) as an intermediary layer between users and the complex database infrastructure. The TPM translates user-friendly data fabric configurations into executable database operations, shielding users from database complexity while maintaining full functionality. This intermediary absorbs the complexity and presents a simplified interface to users.
2Productivity
If database administrators manually manage data platform changes, then data can be accessed and processed, but resource utilization becomes redundant and efficiency decreases
Solution Approach 1:
The patent implements preliminary action by pre-configuring data fabric configurations with predefined templates and patterns for common data ingestion and consumption scenarios. Users can select from these pre-defined configurations rather than building everything from scratch, significantly reducing the time and resources required for data platform setup and modification.
Solution Approach 2:
By enabling users to self-configure data management operations through the TPM interface, the system eliminates redundant work performed by database administrators on routine tasks. Users can independently provision, modify, and consume data services without requiring manual intervention from specialized staff, thereby improving productivity and reducing resource utilization redundancy.
Data Source
AI summary
Example methods, apparatuses, and systems are disclosed for ingesting and consuming data utilizing a trading partner manager. In one example embodiment, an example computing device receives user input comprising a set of data fabric configurations. The computing device then receives, into a data landing zone and based on the data fabric configurations, a data set from a data source. The computing device then ingests, based on the data fabric configurations, the received data set from the data landing zone into a data lake. The computing device then enriches, based on the data fabric configurations, the ingested data set. The computing device then enables data consumption of the ingested data set by the user.