External system integration into automated attribute discovery

an external system and attribute technology, applied in the field of external system integration into automated attribute discovery, can solve the problems of expensive and time-consuming manual collection of such data on a periodic basis, and it is difficult to know this for large companies and governmental entities

Inactive Publication Date: 2009-06-04
PANWAR RAJENDRA BHAGWATISINGH +1
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AI Technical Summary

Benefits of technology

This patent describes how software can be used to create customized forms for different companies or systems. It involves generating reports that contain all the necessary information about a company's attributes and storing them in a central database. These reports then get translated into specific formats based on the needs of the new system. Export adaptors are also involved in this process, ensuring seamless integration of the new system. Overall, this technology allows for more efficient and automated form development without requiring significant human effort.

Problems solved by technology

The technical problem addressed in this patent text is the difficulty of manually gathering accurate information about a large number of assets owned by organizations. Companies often struggle to keep track of these assets because it takes too much money and resources to constantly update the information. To address this issue, various automatic inventory collection tools have been created, such as BDNAs Automated Inventory Software. However, when trying to integrate these new tools with existing enterprise resource planning (ERP) systems, issues arise due to differences in data models and semantics. Therefore, the patent proposes a solution to enable seamless integration of these two kinds of data sets while maintaining the privacy and security of the organization's own data.

Method used

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  • External system integration into automated attribute discovery
  • External system integration into automated attribute discovery
  • External system integration into automated attribute discovery

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Embodiment Construction

[0053]The process of exporting inventory attribute data developed by systems such as those marketed by BDNA (hereafter BDNA discovered data) into the data bases or data structures of other system fundamentally involves a mapping process to resolve differences between the data structure (data model) of the BDNA discovered data and the data structure or data model of a target system.

[0054]FIG. 1 is one page of a multipage data model diagram illustrating some of the Configuration Items in the IBM CMDB data model. This is a conceptual model only in the form of a class diagram and is not how the data is actually stored in their database. A CMDB is a common store where all the information about the IT assets of an entity are stored, and it has a data structure or data model which is independent of the data structure of discovery data discovered by discovery tools such as the BDNA discovery tool. A data model is a class diagram which defines the classes of objects, each object's attributes...

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Abstract

Methods and apparatus to transform attribute data about assets in a source system data model into attribute data about the same assets in a target system data model. The first step is to extract the necessary attribute data from attribute data collected about inventory assets of a business entity needed to populate the attributes in objects representing those inventory assets in a target system data model. Transformation rules are written which are designed to make all conversions necessary in semantics, units of measure, etc. to transform the source system attribute data into attribute data for the target system which has the proper data format. These transformation rules are executed on a computer on the extracted attribute data and the transformed attribute data is stored in an ER model. In the preferred embodiment, the transformation rules are object-oriented in that transformation rules for subtypes can be inherited from their parent types or classes. An export adapter which is capable of invoking the application programmatic interface of the target system CMDB is then used to export the transformed attribute data stored in the ER model to the target system CMDB. A heuristic method to create self-consistent data blocks without exceeding a maximum size limit involves loading instances of entity types and all related instances in the order of decreasing connectivity metric.

Description

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Claims

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Application Information

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Owner PANWAR RAJENDRA BHAGWATISINGH
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