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Erschienen in: Business & Information Systems Engineering 1/2020

06.08.2018 | Research Paper

Designing Business Analytics Solutions

A Model-Driven Approach

verfasst von: Soroosh Nalchigar, Eric Yu

Erschienen in: Business & Information Systems Engineering | Ausgabe 1/2020

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Abstract

The design and development of data analytics systems, as a new type of information systems, has proven to be complicated and challenging. Model based approaches from information systems engineering can potentially provide methods, techniques, and tools for facilitating and supporting such processes. The contribution of this paper is twofold. Firstly, it introduces a conceptual modeling framework for the design and development of advanced analytics systems. It illustrates the framework through a case and provides a sample methodological approach for using the framework. The paper demonstrates potential benefits of the framework for requirements elicitation, clarification, and design of analytical solutions. Secondly, the paper presents some observations and lessons learned from an application of the framework by an experienced practitioner not involved in the original development of the framework. The findings were then used to develop a set of guidelines for enhancing the understandability and effective usage of the framework.

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Fußnoten
1
Due to space limitations, actors are not shown in Fig. 2. See Nalchigar and Yu (2018) for instantiations of this element.
 
2
Assuming that the Accuracy metric has the highest priority among the metrics and softgoals.
 
3
Due to space limitations, the model in Fig. 2 is showing only one of the classification goals. There can be several classification models for predicting user churn each with different prediction periods and time intervals.
 
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Metadaten
Titel
Designing Business Analytics Solutions
A Model-Driven Approach
verfasst von
Soroosh Nalchigar
Eric Yu
Publikationsdatum
06.08.2018
Verlag
Springer Fachmedien Wiesbaden
Erschienen in
Business & Information Systems Engineering / Ausgabe 1/2020
Print ISSN: 2363-7005
Elektronische ISSN: 1867-0202
DOI
https://doi.org/10.1007/s12599-018-0555-z

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