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Title: From requirements to data analytics process: An ontology-based approach
Authors: Bandara, Madhushi
Behnaz, Ali
Rabhi, Fethi A.
Demirörs, Onur
Keywords: Analytics process
Publisher: Springer
Abstract: Comprehensively describing data analytics requirements is becoming an integral part of developing enterprise information systems. It is a challenging task for analysts to completely elicit all requirements shared by the organization’s decision makers. With a multitude of data available from e-commerce sites, social media and data warehouses selecting the correct set of data and suitable techniques for an analysis itself is difficult and time-consuming. The reason is that analysts have to comprehend multiple dimensions such as existing analytics techniques, background knowledge in the domain of interest and the quality of available data. In this paper, we propose to use semantic models to represent different spheres of knowledge related to data analytics space and use them to assist in analytics requirements definition. By following this approach users can create a sound analytics requirements specification, linked with concepts from the operation domain, available data, analytics techniques and their implementations. Such requirements specifications can be used to drive the creation and management of analytics solutions, well aligned with organizational objectives. We demonstrate the capabilities of the proposed method by applying on a data analytics project for house price prediction. © 2019, Springer Nature Switzerland AG.
Description: 16th International Conference on Business Process Management, BPM International Workshops 2018 -- 9 September 2018 through 14 September 2018
ISBN: 9783030116408
ISSN: 1865-1348
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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