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Organisations are currently dealing with huge and growing volumes and varieties of data. Only a small proportion of this data is transformed into knowledge. To this end, many companies are using BIG DATA techniques. This research presents a literature review of studies and research in the fields of Knowledge Management (KM) and BIG DATA over the last ten years. The aim of this study is to identify the concepts, applications, purposes and processes related to the subject and to identify the most important Critical Success Factors in BIG DATA applications in order to minimise the risks of its…mehr

Produktbeschreibung
Organisations are currently dealing with huge and growing volumes and varieties of data. Only a small proportion of this data is transformed into knowledge. To this end, many companies are using BIG DATA techniques. This research presents a literature review of studies and research in the fields of Knowledge Management (KM) and BIG DATA over the last ten years. The aim of this study is to identify the concepts, applications, purposes and processes related to the subject and to identify the most important Critical Success Factors in BIG DATA applications in order to minimise the risks of its application. A case study in a large national logistics company confirmed the main components of a KM model applicable to BIG DATA and that the Critical Success Factors of KM are equally important for minimising the risks of BIG DATA applications. The result of this research also presents the practical implications in terms of what gaps exist in relation to the Critical Success Factors for thecompany under analysis and the relevant considerations.
Autorenporträt
Antonio Braquehais has a degree in Business Administration, specialising in Information Technology Management from the University of Brasilia (UnB) and a master's degree in Electronic Business from the University of Ottawa (Canada). He has a Master's degree in Knowledge Management and Information Technology from the Catholic University of Brasilia.