Abstract
Through data analytics, enterprises can exploit the value their data hold. However, there are still various challenges to be solved, one of them being how to consume data in heterogeneous data management landscapes. To address this challenge, we developed a systematic, hierarchical approach to data consumption, including six data consumption patterns, which is presented in this paper. Each of the six patterns can be associated with multiple implementation patterns that detail its technical realization. We report the application of these patterns in a real-world practical scenario and discuss the benefits of applying the data consumption patterns.
Published Version
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