Crisp-dm/smes: A data analytics methodology for non-profit smes
The exponential increase in information due to technological advances and the development of communications has created the need to make decisions based on the data analysis. This trend has opened the doors to new approaches to data understanding and decision-making. On the one hand, companies need...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2020
- Institución:
- Universidad de Medellín
- Repositorio:
- Repositorio UDEM
- Idioma:
- eng
- OAI Identifier:
- oai:repository.udem.edu.co:11407/5769
- Acceso en línea:
- http://hdl.handle.net/11407/5769
- Palabra clave:
- CRISP-DM
Data analytics
Non-profit SMEs
Cost engineering
Decision making
Profitability
Software design
CRISP-DM
Exponential increase
Implementation cost
Non-profit
Reference frameworks
Small and medium-sized enterprise
Software process engineering metamodel
Technological advances
Data Analytics
- Rights
- License
- http://purl.org/coar/access_right/c_16ec
Summary: | The exponential increase in information due to technological advances and the development of communications has created the need to make decisions based on the data analysis. This trend has opened the doors to new approaches to data understanding and decision-making. On the one hand, companies need to follow data analytic methodologies to manage large volumes of information with big data tools. On the other hand, there are non-profit small and medium-sized enterprises (SMEs) that make efforts to address data analytics according to their different sources and types. They find challenges such as lack of knowledge in methodological and software tools, which allow timely deployment for decision-making. In this paper, we propose a data analytics methodology for non-profit SMEs. The design of this methodology is based on CRISP-DM as a reference framework, is represented by Software Process Engineering Metamodel (SPEM) and is characterized by being simple, flexible, and low implementation costs. © Springer Nature Singapore Pte Ltd. 2020. |
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