Towards a Taxonomy for Big Data Technological Ecosystem

Vitor Pinto, Fernando Parreiras

Abstract

Data is constantly created, and at an ever-increasing rate. Intending to be more and more data-driven, companies are struggling to adopt Big Data technologies. Nevertheless, choosing an appropriate technology to deal with specific business requirements becomes a complex task, specially because it involves different kinds of specialists. Additionally, the term Big Data is vague and ill defined. This lack of concepts and standards creates a fuzzy environment where companies do not know what exactly they need to do and on the other hand consultants do not know how to help them to achieve their goals. In this study the following research question was addressed: Which essential components characterize Big Data ecosystem? To answer this question, Big Data terms and concepts were first identified. Next, all terms and concepts were related and grouped creating a hierarchical taxonomy. Thus, this artifact was validated through a classification of tools available in the market. This work contributes to clarification of terminologies related to Big Data, facilitating its dissemination and usage across research fields. The results of this study can contribute to reduce time and costs for Big Data adoption in different industries as it helps to establish a common ground for the parts involved.

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Paper Citation


in Harvard Style

Pinto V. and Parreiras F. (2020). Towards a Taxonomy for Big Data Technological Ecosystem.In Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-423-7, pages 294-305. DOI: 10.5220/0009416302940305


in Bibtex Style

@conference{iceis20,
author={Vitor Pinto and Fernando Parreiras},
title={Towards a Taxonomy for Big Data Technological Ecosystem},
booktitle={Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2020},
pages={294-305},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009416302940305},
isbn={978-989-758-423-7},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Towards a Taxonomy for Big Data Technological Ecosystem
SN - 978-989-758-423-7
AU - Pinto V.
AU - Parreiras F.
PY - 2020
SP - 294
EP - 305
DO - 10.5220/0009416302940305