Electronic Data Feed Validation System for Inventory Accuracy
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Solution Overview
Problem
The existing systems for electronic data feeds in eCommerce environments face inefficiencies due to duplicate data rebroadcasting and anomalies in inventory transactions across multiple eCommerce sites, leading to computing resource inefficiency and slower processing.
Innovation Solution
A system comprising a feed gateway, messaging management unit, and inventory management unit that processes inventory messages, validates data, and generates responses to eliminate duplicates and anomalies, ensuring accurate inventory updates and reducing redundant data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vendors replay all transactions to each eCommerce site to ensure latest inventory count, then inventory accuracy is improved, but computing resource consumption increases
Solution Approach 1:
The patent extracts only the essential validation information (anomaly detection, duplicate identification) from the complete transaction replay process. The MMU extracts and validates key message properties without requiring full transaction reprocessing, reducing computing resources while maintaining inventory accuracy through targeted validation checks.
Solution Approach 2:
The system performs preliminary validation actions at the MMU before full inventory updates are processed. By pre-validating messages for anomalies and duplicates in the message queue, the system prevents unnecessary processing of invalid data, reducing overall computing resource consumption while ensuring only valid transactions update inventory counts.
2Reliability
If vendors rebroadcast inventory data across multiple sites to eliminate anomalies, then data accuracy is improved, but processing speed deteriorates
Solution Approach 1:
The messaging management unit acts as an intermediary between feed gateways and the inventory management system. It performs validation, anomaly detection, and duplicate identification in the message queue before data reaches the IMS, enabling parallel processing of multiple vendor feeds simultaneously without blocking inventory updates, thus maintaining both accuracy and processing speed.
Solution Approach 2:
The system segments the validation process into independent operations at the MMU level. Each message is validated separately for anomalies and duplicates before being processed by the IMS, allowing concurrent processing of multiple inventory updates without sequential bottlenecks, thereby maintaining high processing speed while ensuring data accuracy.
3Reliability
If the system validates each inventory message individually, then data quality is improved, but processing time increases
Solution Approach 1:
The validation process operates continuously in the message queue without interrupting the flow of inventory updates. The MMU performs anomaly detection and duplicate identification as continuous background operations on incoming messages, rather than batch processing, maintaining uninterrupted data flow and minimizing processing time delays while ensuring comprehensive validation of each message.
Data Source
AI summary
A method includes receiving an electronic feed inventory file; creating a feed message including a batch of inventory messages based on the feed inventory file; placing the feed message in a message queue; performing validation of each of the inventory messages; generating a response to each invalid inventory messages; generating a first batch of response message including the responses to the invalid inventory messages; publishing the first batch of response message to the message queue; updating a first database based on validated inventory messages; generating responses to each of the validated inventory messages; generating a second batch of response message including the responses to the validated inventory messages, the first and second batch of response message having the batch identification; publishing the second batch of response message to the message queue; and updating a second database based on the first and second batch of response messages.