ERP Data Population Platform for Regulatory Reporting Sync
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Solution Overview
Problem
Existing technologies lack a seamless and automated method for extracting data from a source ERP application and populating it into a target ERP application for regulatory compliance across different regions, which is error-prone and time-consuming, failing to meet dynamic regulatory reporting needs.
Innovation Solution
A data population platform establishes connections with both source and target ERP applications, receives user inputs to extract and share ERP data, synchronizes data in near-real time or predefined intervals, and ensures data parity to maintain consistent configuration and customization across devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data extraction and population methods are used between ERP systems, then data can be transferred between source and target systems, but the process is error-prone and time-consuming
Solution Approach 1:
The system enables automated self-service data extraction and population between ERP systems through configured extraction rules and criteria. The source ERP system automatically identifies and extracts data based on predefined criteria without manual intervention, populating the target ERP system while maintaining data accuracy and reducing transfer time.
Solution Approach 2:
The patent introduces an intermediary extraction mechanism that mediates between source and target ERP systems. This intermediary layer applies extraction rules and criteria to automatically transfer data, reducing manual errors and improving efficiency while maintaining data integrity across systems.
2Productivity
If automated data extraction is implemented, then data transfer efficiency improves, but system complexity increases
Solution Approach 1:
The system manages complexity by allowing parameter changes in extraction rules and criteria without requiring system reconfiguration. Users can modify extraction parameters such as data fields, filters, and targets through configuration interfaces, enabling flexible automated data transfer while maintaining manageable system complexity.
3Adaptability or versatility
If comprehensive data extraction is performed to meet all regulatory requirements, then compliance coverage is improved, but data processing time increases
Solution Approach 1:
The system applies partial action by extracting only the specific data required for regulatory compliance based on predefined criteria and rules. Rather than extracting all possible data, the system identifies and extracts only the necessary portions, improving compliance coverage while reducing processing time through targeted data extraction.
Solution Approach 2:
The extraction system is dynamic, allowing extraction criteria and rules to be adjusted based on specific regulatory requirements. The system can adapt extraction parameters, filters, and targets dynamically to meet different compliance needs without requiring complete re-extraction, thus improving compliance coverage efficiently.
Data Source
AI summary
Embodiments herein provide a method for handling an ERP data. The method includes establishing, by a data population platform, a connection with at least one source electronic device in which at least one ERP application is executed. Further, the method includes establishing, by the data population platform, a connection with at least one target electronic device in which at least one ERP application is executed. Further, the method includes receiving, by the data population platform, a request including at least one user input from the at least one target electronic device to obtain the ERP data from the at least one source electronic device. Further, the method includes obtaining, by the data population platform, the ERP data from the at least one source electronic device based on the request. Further, the method includes sharing, by the data population platform, the ERP data to the at least one target electronic device.