Abstract
Nowadays, adopting a “data culture” or operating “data-driven” are desired goals for a number of managers. However, what does it mean when an organization claims to have data culture? A clear definition is not available. This paper aims to sharpen the understanding of data culture in organizations by discussing recent usages of the term. It shows that data culture is a kind of organizational culture. A special form of data culture is a data-driven culture. We conclude that a data-driven culture is defined by following a specific set of values, behaviors and norms that enable effective data analytics. Besides these values, behaviors and norms, this paper presents the job roles necessary for a datadriven culture. We include the crucial role of the data steward that elevates a data culture to a data-driven culture by administering data governance. Finally, we propose a definition of data-driven culture that focuses on the commitment to data-based decision making and an ever-improving data analytics process. This paper helps teams and organizations of any size that strive towards advancing their – not necessarily big – data analytics capabilities by drawing their attention to the often neglected, non-technical requirements: data governance and a suitable organizational culture.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature
About this paper
Cite this paper
Kremser, W., Brunauer, R. (2019). Do we have a Data Culture?. In: Haber, P., Lampoltshammer, T., Mayr, M. (eds) Data Science – Analytics and Applications. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-27495-5_11
Download citation
DOI: https://doi.org/10.1007/978-3-658-27495-5_11
Published:
Publisher Name: Springer Vieweg, Wiesbaden
Print ISBN: 978-3-658-27494-8
Online ISBN: 978-3-658-27495-5
eBook Packages: Computer Science and Engineering (German Language)