Big data in industry 4.0 is a major subject for the currently developed research but also for the organizations that are motivated to invest in these kinds of projects. The big data are known as the large quantity of data collected from various resources that potentially could be analyzed and provide valuable insights and patterns. In industry 4.0 the production of data is massive, and thus, provides the basis for analysis and important information extraction. This study aims to provide the impact of big data analytics in industry 4.0 environments by the utilization of the SWOT dimensions framework with the intention to provide both a positive and a negative perspective of the subject. Considering that these implementations are an innovative trend and limited awareness exists for the subject, it is valuable to summarize and explore the identified findings from the published literature that will be reviewed based on interviews with data scientists. The intention is to increase the knowledge of the subject and inform the organizations about their potential expectations and challenges. The effects are represented in the SWOT analysis based on findings collected from 22 selected articles which were afterwards discussed with professionals. The systematic literature review started with the creation of a plan and specifically defined steps approach based on previously existing scientific papers. The relevant literature was decided upon specified inclusion and exclusion criteria and their relevance to the research questions. Following this, the interview questionnaire was build based on the findings in order to gather empirical data on the subject. The results revealed that the insights developed through big data support the management towards effective decision-making since it reduces the ambiguity of the actions. Meanwhile, the optimization of production, expenditure decrement, and customer satisfaction are the following as top categories mentioned in the selected articles for the strength dimension. In the opportunities, the interoperability of the equipment, the real-time information acquirement and exchange, and self-awareness of the systems are reflected in the majority of the papers. On the contrary, the threats and weaknesses are referred to fewer studies. The infrastructure limitations, security, and privacy issues are demonstrated substantially. The organizational changes and human resources matters are also expressed but infrequently. The data scientists agreed with the findings and mentioned that decision-making, process effectiveness and customer relationships are their major expectations and objectives while the experience and knowledge limitations of the personnel is their main concern. In general, the gaps in the existing literature could be identified in the challenges that occur for the big data projects in industry 4.0. Consequently, further research is recommended in the field in order to raise the awareness in the interested parties and ensure the project’s success.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-99443 |
| Date | January 2020 |
| Creators | Oikonomidi, Sofia |
| Publisher | Linnéuniversitetet, Institutionen för informatik (IK) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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