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Skills Sets Towards Becoming Effective Data Scientists

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 731))

Abstract

The tsunami of data and information brings with it challenges in decision making to organisations especially so to the government sector. Decision making is vital in ensuring effective service delivery to constituents. Nowadays, Big Data Analytics (BDA) tools and software are readily available but what is lacking are the skills and competency of the personnel to handle and manage these data. The Government of Malaysia requires its IT officers to assume a more important role to extract data and turn into valuable information which is beneficial to operations and planning. However initial findings revealed that these IT officers are lacking in data scientist skills. Therefore, there is a need to propose a guideline on the direction towards acquirement of these skills to become data scientists. This paper presents the findings conducted recently via experts’ views using the Delphi technique, regarding data scientist skills required by the Government IT officers. The findings revealed 46 in-service skill sets which are deemed mandatory for IT officers to have, of which the top seven being analysis, data visualisation, data modelling, decision making, ethics, communication and basic database knowledge and skills. This data is helpful towards building a Data Scientist Competency Development Roadmap for the next five years as a stop gap measure before data scientists graduates are churned from universities.

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Acknowledgments

This study is funded by Advanced Informatics School, Universiti Teknologi Malaysia (UTM AIS).

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Correspondence to Wardah Zainal Abidin .

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Abidin, W.Z., Ismail, N.A., Maarop, N., Alias, R.A. (2017). Skills Sets Towards Becoming Effective Data Scientists. In: Uden, L., Lu, W., Ting, IH. (eds) Knowledge Management in Organizations. KMO 2017. Communications in Computer and Information Science, vol 731. Springer, Cham. https://doi.org/10.1007/978-3-319-62698-7_9

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  • DOI: https://doi.org/10.1007/978-3-319-62698-7_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62697-0

  • Online ISBN: 978-3-319-62698-7

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