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Agile Analytics: How organizations can benefit from the agile methodology for smoother delivery of data-driven analytics projects

  • Despite the inception of new technologies at a breakneck pace, many analytics projects fail mainly due to the use of incompatible development methodologies. As big data analytics projects are different from software development projects, the methodologies used in software development projects could not be applied in the same fashion to analytics projects. The traditional agile project management approaches to the projects do not consider the complexities involved in the analytics. In this thesis, the challenges involved in generalizing the application of agile methodologies will be evaluated, and some suitable agile frameworks which are more compatible with the analytics project will be explored and recommended. The standard practices and approaches which are currently applied in the industry for analytics projects will be discussed concerning enablers and success factors for agile adaption. In the end, after the comprehensive discussion and analysis of the problem and complexities, a framework will be recommended that copes best with the discussed challenges and complexities and is generally well suited for the most data-intensive analytics projects.

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Author:Rafi Ullah
Referee:Denisse Mendoza Almanzar, Harald F. O. von Korflesch
Advisor:Denisse Mendoza Almanzar
Document Type:Master's Thesis
Date of completion:2019/08/30
Date of publication:2019/09/02
Publishing institution:Universität Koblenz, Universitätsbibliothek
Granting institution:Universität Koblenz, Fachbereich 4
Date of final exam:2019/12/20
Release Date:2019/09/02
Number of pages:viii, 97
Institutes:Fachbereich 4 / Institut für Management
Licence (German):License LogoEs gilt das deutsche Urheberrecht: § 53 UrhG