Asset Data Integration via Prestaging Tables
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Solution Overview
Problem
Large organizations face challenges in tracking and accounting for assets due to the complexity of integrating asset tracking data from third-party discovery applications into asset management systems, often requiring custom integrations and significant resources, which increases the total cost of ownership and can lead to data errors.
Innovation Solution
The integration of asset data into asset management systems is facilitated using a Web service or manual load, eliminating the need for a request-response model by employing prestaging tables for data validation and error handling, allowing for streamlined data integration and reconciliation processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a request-response model is used to integrate discovery applications with asset management systems, then data integration can be achieved, but the complexity of integration increases and requires custom development by third-party vendors or systems integrators
Solution Approach 1:
The patent introduces prestaging tables as an intermediary component between discovery applications and the asset management system. These tables serve as a buffer that receives discovery data directly without requiring complex request-response integration logic. The prestaging tables simplify the integration architecture by decoupling the data ingestion process from the data processing process, allowing discovery applications to dump data directly into standardized table structures that the asset management system can then process independently.
Solution Approach 2:
The patent segments the data integration process into distinct stages: data collection in prestaging tables, data validation, data processing, and data reconciliation. This segmentation allows each component to be developed and maintained independently, reducing overall integration complexity. The prestaging tables represent a separate, standardized layer that isolates the complexity of data processing from the discovery application interface.
2Adaptability or versatility
If custom integrations are built to connect discovery applications with asset management systems, then data can be loaded into the system, but the total cost of ownership increases due to vendor involvement and custom development
Solution Approach 1:
The prestaging tables provide a universal data intake mechanism that can accept discovery data from multiple different discovery applications without requiring custom integration logic for each vendor. The standardized table structure and data formats allow any discovery application to load data directly into the asset management system using the same interface, eliminating the need for vendor-specific custom development and reducing ongoing operational costs.
3Productivity
If data is loaded directly into the asset management system without validation, then data processing speed increases, but data integrity and error handling deteriorate
Solution Approach 1:
The patent implements preliminary data validation and error checking that occurs automatically as data is loaded into the prestaging tables and during the subsequent data processing stages. Validation rules check for data quality issues, formatting errors, and completeness requirements before data is processed further. This preliminary action ensures data integrity is maintained without significantly impacting processing speed, as the validation is integrated into the data flow rather than adding separate manual review steps.
Data Source
AI summary
Asset data is loaded or entered into an asset management system using a Web service or a manual load, or both. The asset data may be discovered using a third-party asset discovery application. As a first loading option, an inbound asynchronous Web service is used to process the discovered data. As a second loading option, exposed tables are used for loading discovered data and processing through a run control. These entry points provide for additional data validation and error handling of invalid data. They provide ways for data to enter the asset management system and can also streamline the data integration, the reconciliation processes, and additionally automatically address or fix specific exceptions.