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Automated Interpretation of Key Performance Indicators by Using Rules

Automated Interpretation of Key Performance Indicators by Using Rules

Bojan Tomic
Copyright: © 2009 |Pages: 22
ISBN13: 9781605664026|ISBN10: 1605664022|EISBN13: 9781605664033
DOI: 10.4018/978-1-60566-402-6.ch026
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MLA

Tomic, Bojan. "Automated Interpretation of Key Performance Indicators by Using Rules." Handbook of Research on Emerging Rule-Based Languages and Technologies: Open Solutions and Approaches, edited by Adrian Giurca, et al., IGI Global, 2009, pp. 625-646. https://doi.org/10.4018/978-1-60566-402-6.ch026

APA

Tomic, B. (2009). Automated Interpretation of Key Performance Indicators by Using Rules. In A. Giurca, D. Gasevic, & K. Taveter (Eds.), Handbook of Research on Emerging Rule-Based Languages and Technologies: Open Solutions and Approaches (pp. 625-646). IGI Global. https://doi.org/10.4018/978-1-60566-402-6.ch026

Chicago

Tomic, Bojan. "Automated Interpretation of Key Performance Indicators by Using Rules." In Handbook of Research on Emerging Rule-Based Languages and Technologies: Open Solutions and Approaches, edited by Adrian Giurca, Dragan Gasevic, and Kuldar Taveter, 625-646. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-402-6.ch026

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Abstract

Business reporting is an essential task for every enterprise. In order to make appropriate decisions, decision makers need quality reports. Some recent articles suggest that reports generated by BI (Business Intelligence) systems contain mostly data (key performance indicator values) and little or no information. Data has no meaning and must be interpreted in order to become information. Information is, naturally, much more useful because it directly contributes to recipients’ knowledge and can be acted upon. The consequence is that it is left to the decision maker to manually analyze large quantities of data presented in individual reports in order to derive information. A potential solution for automated business data interpretation is presented in this chapter. It proposes using rules to capture and formalize business knowledge and then utilizing these rules to infer information from data automatically.

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