Approaching the (Big) Data Science Engineering Process

Matthias Volk, Daniel Staegemann, Sascha Bosse, Robert Häusler, Klaus Turowski

2020

Abstract

For many years now, researchers as well as practitioners are harnessing well-known data mining processes, such as the CRISP-DM or KDD, to realize their data analytics projects. In times of big data and data science, at which not only the volume, variety and velocity of the data increases, but also the complexity to process, store and manage them, conventional solutions are often not sufficient and even more sophisticated systems are needed. To overcome this situation, in this positioning paper the (big) data science engineering process is introduced to provide a guideline for the realization of data-intensive systems. For this purpose, using the design science research methodology, existing theory and current literature from relevant subdomains are contextualized, discussed and adapted.

Paper Citation

in Harvard Style

Volk M., Staegemann D., Bosse S., Häusler R. and Turowski K. (2020). Approaching the (Big) Data Science Engineering Process.In Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-426-8, pages 428-435. DOI: 10.5220/0009569804280435

in Bibtex Style

@conference{iotbds20,
author={Matthias Volk and Daniel Staegemann and Sascha Bosse and Robert Häusler and Klaus Turowski},
title={Approaching the (Big) Data Science Engineering Process},
booktitle={Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2020},
pages={428-435},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009569804280435},
isbn={978-989-758-426-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - Approaching the (Big) Data Science Engineering Process
SN - 978-989-758-426-8
AU - Volk M.
AU - Staegemann D.
AU - Bosse S.
AU - Häusler R.
AU - Turowski K.
PY - 2020
SP - 428
EP - 435
DO - 10.5220/0009569804280435