Big Data Technologies and Applications. 8th International Conference, BDTA 2017, Gwangju, South Korea, November 23–24, 2017, Proceedings

Research Article

Mining IT Job-Order Services: Basis for Policy Formulation & IT Resource Allocation

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  • @INPROCEEDINGS{10.1007/978-3-319-98752-1_11,
        author={Alvin Virata and Jasmin Niguidula},
        title={Mining IT Job-Order Services: Basis for Policy Formulation \& IT Resource Allocation},
        proceedings={Big Data Technologies and Applications. 8th International Conference, BDTA 2017, Gwangju, South Korea, November 23--24, 2017, Proceedings},
        proceedings_a={BDTA},
        year={2018},
        month={11},
        keywords={Predictive analytics Resource management Policy improvements},
        doi={10.1007/978-3-319-98752-1_11}
    }
    
  • Alvin Virata
    Jasmin Niguidula
    Year: 2018
    Mining IT Job-Order Services: Basis for Policy Formulation & IT Resource Allocation
    BDTA
    Springer
    DOI: 10.1007/978-3-319-98752-1_11
Alvin Virata1,*, Jasmin Niguidula2,*
  • 1: St. Dominic College of Asia
  • 2: Technological Institute of the Philippines
*Contact email: ajavirata.7772011@gmail.com, jasniguidula@yahoo.com

Abstract

As the computer hardware have been globally accepted in the areas of industry and education, the IT Job- Order Service Delivery are now becoming very essential part in the resources management. With fast-paced technology development, decision makers require a valid reporting IT resources management [1]. IT resources were expected to be fully maintained to ensure the long-term life span of the computer hardware and devices. Further, having an IT Resource Management System or Software will not be sufficient since maintenance and repairs may probably be a burden to the budget allocation when there is a demand for IT infrastructure development or innovation [2]. Determining the instances of IT Job Order Services, its trends of repairs and services conducted has a significant implication to the decision makers. Using a predictive analytics of the data sets in the IT Job-Order services, could be a basis for revising the policy and IT resource allocation.