Authors:
Matthias Volk
;
Daniel Staegemann
;
Akanksha Saxena
;
Johannes Hintsch
;
Naoum Jamous
and
Klaus Turowski
Affiliation:
Magdeburg Research and Competence Cluster (MRCC), Otto-von-Guericke University, Magdeburg, Germany
Keyword(s):
Big Data, Project, Use Case, Architecture, Technologies, Design Science Research.
Abstract:
For almost a decade now, big data has become the foundation of today’s data-intensive systems used for various disciplines, such as data science or artificial intelligence. Although a certain level of maturity has been reached since then, not only in the domain itself but also in the engineering of interconnected systems, many problems still exist today. The number of available technologies and architectural concepts, whose application is often very use case-specific, makes the successful implementation of big data projects still a non-trivial undertaking. To overcome this problem and deliver support with the realization of a related project, existing standard use cases in this domain are analyzed, and architectural concepts are derived through the design science research methodology. By observing essential criteria, like use case descriptions as well as relevant requirements, decision-makers can harness architectural concepts and technology recommendations for their setup.