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Author: Lito Perez Cruz

Affiliation: Monash University, Australia

ISBN: 978-989-758-272-1

Keyword(s): Data Science, Data Analytics, Software Engineering, Education.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Domain Analysis and Modeling ; Education and Training ; Expert Systems ; Health Engineering and Technology Applications ; Health Information Systems ; Knowledge Acquisition ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Simulation and Modeling ; Simulation Tools and Platforms ; Symbolic Systems

Abstract: Data science is strongly related to knowledge discovery. It can be said that the output of the data science work is input to the knowledge discovery process. With data science evolving as a discipline of its own, it is estimated that the U.S.A alone, needs more than 1M professionals skilled in the discipline by next year. If we include the needs of the rest of the world, then internationally, it needs more than that. Consequently, private and public educational institutions are hurriedly offering data science courses to candidates. The general emphasis of these courses understandably, is in the use of data mining and machine learning tools and methods. In this paper, we will argue that the subject of software engineering should also be taught to these candidates formally, and not haphazardly, as if it is something the would-be data scientist can pick up along the way. In this paper, we will examine the data science work process and the present state of skills training provide d by data science educators. We will present warrants and arguments that software engineering as a discipline can not be taken for granted in the training of a data scientist. (More)

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Paper citation in several formats:
Cruz, L. (2017). When Data Science Becomes Software Engineering.In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, ISBN 978-989-758-272-1, pages 226-232. DOI: 10.5220/0006508502260232

@conference{keod17,
author={Lito Perez Cruz.},
title={When Data Science Becomes Software Engineering},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD,},
year={2017},
pages={226-232},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006508502260232},
isbn={978-989-758-272-1},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD,
TI - When Data Science Becomes Software Engineering
SN - 978-989-758-272-1
AU - Cruz, L.
PY - 2017
SP - 226
EP - 232
DO - 10.5220/0006508502260232

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