Data Strategy Development: A Taxonomy for Data Strategy Tools and Methodologies in the Economy

Inan Gür (), Markus Spiekermann (), Michael Arbter () and Boris Otto ()
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Inan Gür: Fraunhofer Institute for Software and Systems Engineering
Markus Spiekermann: Fraunhofer Institute for Software and Systems Engineering
Michael Arbter: Fraunhofer Institute for Software and Systems Engineering
Boris Otto: Fraunhofer Institute for Software and Systems Engineering

A chapter in Innovation Through Information Systems, 2021, pp 448-461 from Springer

Abstract: Abstract Data are a key driver of the digital era. They shift the strategic landscape of organizations and change how companies approach their business. Nevertheless, existing approaches on data strategies vary vastly and little common ground is visible. Therefore, we develop a comprehensive taxonomy for data strategy tools and methodologies in order to identify characteristics and relevant properties of data strategy. We derived the taxonomy inductively by analyzing existing data strategy tools and methodologies offered in the current economy and deductively by conducting a structured literature review on the existing body of knowledge in the scientific literature. It serves as a scientific instrument to profoundly assess and create data strategies and work towards a consensus in the respective research field.

Keywords: Data strategy; Digital strategy; IT-strategy; Taxonomy (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-030-86790-4_30

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DOI: 10.1007/978-3-030-86790-4_30

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