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How to Structure a Company-wide Adoption of Big Data Analytics

Title data

Bürger, Olga:
How to Structure a Company-wide Adoption of Big Data Analytics.
2019
Event: 14th International Conference on Wirtschaftsinformatik (WI) , 24.-27.2.2019 , Siegen, Germany.
(Conference item: Conference , Paper )

Official URL: Volltext

Project information

Project title:
Project's official titleProject's id
Projektgruppe WI Künstliche IntelligenzNo information

Abstract in another language

Driven by increasing amounts of data and by emerging technologies to store and analyze them, companies adopt Big Data Analytics (BDA) to improve their innovativeness and decision-making. However,adopting BDA across the company in the sense of an insight-driven organization (IDO) is challenging, since it influencesthe entire company and requires an organizational change. Despite mature knowledge, approaches that provide concrete methods for structuring the company-wide adoption of BDA tofully exploit the benefits of BDA andtoreduce the risk of its failureare still missing. Following action design research, we developed and evaluated a method for structuring the company-wide adoption of BDAin a concerted research effort at a German bank. Based on knowledge of BDA and the roadmapping approach, the method structures the adoptionalong the BDA capabilities. We illustrate how companies can define a target state, identify gaps, and derive aBDAroadmap

Further data

Item Type: Conference item (Paper)
Refereed: Yes
Keywords: Big Data Analytics; Roadmapping; Action Design Research
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration VII
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > Fraunhofer Project Group Business and Information Systems Engineering
Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management
Faculties
Faculties > Faculty of Law, Business and Economics
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 06 Mar 2019 07:09
Last Modified: 26 Jun 2019 08:51
URI: https://eref.uni-bayreuth.de/id/eprint/47853