DocumentCode :
3692708
Title :
Analysis of data from the monitoring environment to improve IT processes
Author :
Peter Michalik;Simona Polačková;Iveta Zolotová
Author_Institution :
Dept. of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Koš
fYear :
2015
Firstpage :
427
Lastpage :
433
Abstract :
This article describes the design, comparison and evaluation of predictive models from the area of monitoring data on the basis of CRISP-DM and RadpidMiner technology, for the purpose of improving IT processes in the company. These models have been created on a sample of real data from the monitoring of IT systems in one of the largest companies in Slovakia. Article defines the detailed description and evaluation of created models, which represents only one phase of this research. This means that the other phases are only mentioned - understanding and editing of data, visualization and statistical analysis, along with modeling process itself. Predictive models generated by linear regression and ARIMA models are described in detail in this article. These models achieved during research are a huge benefit for companies, since they can predict the future value of individual transactions, and thus take the necessary measures to make the right decisions in order to improve quality of services.
Keywords :
"Companies","Predictive models","Data models","Monitoring","Correlation","Linear regression","Knowledge discovery"
Publisher :
ieee
Conference_Titel :
Intelligent Engineering Systems (INES), 2015 IEEE 19th International Conference on
Type :
conf
DOI :
10.1109/INES.2015.7329748
Filename :
7329748
Link To Document :
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