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Samsung field lab voids: development of a data science application using agile methodology

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Detalhes bibliográficos
Resumo:VOIDS is a data science student entrepreneurial project that aims to integrate marketing into demand planning, helping companies to achieve the most accurate way of planning and shaping future demand. The following work applies this vision in a lean agile start-up framework, implementing state-of-the-art deep learning time series forecasting techniques in the business context of the global consumer electronic brand Samsung. The individual work discusses the development of a data analytics dashboard. It elaborates why an agile development methodology has been implemented and lays out the selection of the underlying development framework. Furthermore, the resulting application is demonstrated and explained.
Autores principais:Fleer, Jannis Marvin
Assunto:Machine learning Business analytics Demand planning Agile practices Marketing analytics Software development Applied data science
Ano:2022
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso embargado
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL
Descrição
Resumo:VOIDS is a data science student entrepreneurial project that aims to integrate marketing into demand planning, helping companies to achieve the most accurate way of planning and shaping future demand. The following work applies this vision in a lean agile start-up framework, implementing state-of-the-art deep learning time series forecasting techniques in the business context of the global consumer electronic brand Samsung. The individual work discusses the development of a data analytics dashboard. It elaborates why an agile development methodology has been implemented and lays out the selection of the underlying development framework. Furthermore, the resulting application is demonstrated and explained.