Data Extraction Workbench for ERP Systems
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Solution Overview
Problem
Existing ERP systems, such as SAP, face challenges in providing users with a cost-effective, quick, and customizable method for extracting and exporting data, as conventional methods are expensive, resource-intensive, and require significant IT development and hardware resources.
Innovation Solution
The EDL method and system utilize a Data Export Workbench (DEW) and Data Integrator (DI) applications to extract, direct, and load data from ERP systems to predefined destinations, leveraging underutilized hardware and allowing end-users to configure data extraction and export processes without requiring additional hardware or extensive IT development.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional ERP data extraction methods (SAP BI/BO/BW/BODS, ETL platforms, ABAP) are used, then data extraction capability is achieved, but cost and hardware resource requirements increase significantly
Solution Approach 1:
The patent extracts the data extraction functionality from complex, resource-intensive conventional ERP systems and implements it as a separate, lightweight application that can operate independently. This allows data extraction capabilities to be obtained without requiring the full infrastructure of traditional SAP BI/BO/BW/BODS or ETL platforms, thereby reducing hardware resource requirements while maintaining extraction capability.
Solution Approach 2:
The patent employs a simplified, cost-effective data extraction approach that replaces expensive, permanent enterprise-wide data platforms with a more economical solution. The system uses a lightweight application that can perform extraction tasks without requiring costly hardware infrastructure, making the solution more accessible and reducing overall system cost.
2Ease of operation
If standard SAP export utilities (SQVI, SE16) are used, then data access is enabled, but user flexibility and customization capability are limited
Solution Approach 1:
The patent implements a system where end users can independently configure and execute data extraction tasks without requiring IT department intervention or specialized knowledge of SAP ABAP programming. The application provides a user-friendly interface that allows users to define their own extraction criteria, select data sources, and specify output formats, enabling self-service data access while significantly enhancing user flexibility and customization capability.
3Reliability
If conventional ERP data extraction systems are implemented, then data extraction functionality is provided, but development lifecycle time and cost increase
Solution Approach 1:
The patent implements a pre-configured data extraction application that comes with built-in templates, standard extraction patterns, and predefined connectivity options. This preliminary preparation allows users to quickly deploy data extraction functionality without undergoing lengthy development cycles. The system is designed to be ready-to-use with minimal configuration, thereby reducing both development time and associated costs while maintaining reliable data extraction functionality.
4Reliability
If specialized IT development resources are allocated for data extraction, then extraction capability is enhanced, but resource intensity and specialization requirements increase
Solution Approach 1:
The patent extracts the specialized data extraction functionality from the complex ERP system core and places it in a separate, simplified application. This separation eliminates the need for specialized IT development resources to work within the complex SAP ABAP environment, as the standalone application provides extraction capabilities through a more accessible interface, thereby reducing both resource specialization requirements and system complexity.
Data Source
AI summary
A method of extracting data from one or more data sources and loading the data into one or more destinations sources is disclosed. The method can include deploying data engines into one or more user network systems, receiving input with respect to a first data source, receiving input with respect to a second data destination, and receiving input with respect to one or more user-defined data stored on the first data source. The method can further include receiving input with respect to linking the first data source and second data destination to the deployed data engines and pinging, via data engines, for requests to extract and direct the user-defined data from the first data source, and retrieving, via the data engines, the user-defined data from the first data source and storing the retrieved user-defined within an intermediary database to be loaded it into the second data destination.