Towards an Improved ASUM-DM Process Methodology for Cross-Disciplinary Multi-organization Big Data & Analytics Projects

The development of big data & analytics projects with the participation of several corporate divisions and research groups within and among organizations is a non-trivial problem and requires well-defined roles and processes. Since there is no accepted standard for the implementation of big data...

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Bibliographic Details
Published inKnowledge Management in Organizations pp. 613 - 624
Main Authors Angée, Santiago, Lozano-Argel, Silvia I., Montoya-Munera, Edwin N., Ospina-Arango, Juan-David, Tabares-Betancur, Marta S.
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing
SeriesCommunications in Computer and Information Science
Subjects
Analytics
ASUM-DM
Big data
CRISP-DM
Process methodology
Project management
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Summary:The development of big data & analytics projects with the participation of several corporate divisions and research groups within and among organizations is a non-trivial problem and requires well-defined roles and processes. Since there is no accepted standard for the implementation of big data & analytics projects, project managers have to either adapt an existing data mining process methodology or create a new one. This work presents a use case for a big data & analytics project for the banking sector. The authors found out that an adaptation of ASUM-DM, a refined CRISP-DM, with the addition of big data analysis, application prototyping, and prototype evaluation, plus a strong project management work with an emphasis in communications proved the best solution to develop a cross-disciplinary, multi-organization, geographically-distributed big data & analytics project.
ISBN:331995203X
9783319952031
ISSN:1865-0929
1865-0937
DOI:10.1007/978-3-319-95204-8_51