Abstract
Data analytics is an essential element for success in modern enterprises. Nonetheless, to effectively design and implement analytics systems is a non-trivial task. This paper proposes a modeling framework (a set of metamodels and a set of design catalogues) for requirements analysis of data analytics systems. It consists of three complementary modeling views: business view, analytics design view, and data preparation view. These views are linked together and act as a bridge between enterprise strategies, analytics algorithms, and data preparation activities. The framework comes with a set of catalogues that codify and represent an organized body of business analytics design knowledge. The framework has been applied to three real-world case studies and findings are discussed.
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Notes
- 1.
Actors are not shown here due to space limitations.
- 2.
There were several instances of classification goal that each addressed a specific prediction period, such as 8, 16, 24Â h. Each of the goals is connected to a different instance of the insight element. Due to space limitations, only one pair of analytics goal and insight is illustrated here.
- 3.
In the first case study, the indicator Precision had highest priority which justified the choice of Decision Forest for the corresponding classification goal.
- 4.
The company has a cross-platform data center management system that logs computer systems operations.
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Nalchigar, S., Yu, E., Ramani, R. (2016). A Conceptual Modeling Framework for Business Analytics. In: Comyn-Wattiau, I., Tanaka, K., Song, IY., Yamamoto, S., Saeki, M. (eds) Conceptual Modeling. ER 2016. Lecture Notes in Computer Science(), vol 9974. Springer, Cham. https://doi.org/10.1007/978-3-319-46397-1_3
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