التفاصيل البيبلوغرافية
| العنوان: |
A Data-Analytics Approach for Enterprise Resilience. |
| المؤلفون: |
Xu, Donna, Tsang, Ivor W., Chew, Eng K., Siclari, Cosimo, Kaul, Varun |
| المصدر: |
IEEE Intelligent Systems; May-Jun2019, Vol. 34 Issue 3, p6-18, 13p |
| مصطلحات موضوعية: |
DATA mining, BUSINESS analytics, MACHINE learning, BUSINESS enterprises, INTELLIGENT buildings, VISUAL analytics |
| مستخلص: |
Enterprise resilience plays an important role to prevent business services from disruptions caused by human-induced disasters such as failed change implementations and software bugs. Traditional expert-centric approach has difficulty to maintain continued critical business functions because the disasters can often only be handled after their occurrence. This paper introduces a data-analytics approach, which leverages system monitoring data for the enterprise resilience. With the power of data mining and machine learning techniques, we build an intelligent business analytics system to detect the potential disruptions proactively, and to assist the operational team for enterprise resilience enhancement. We demonstrate the effectiveness of our approach on a real enterprise system monitoring dataset in simulation. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
