Big Data and Predictive Data Analytics in the Smes Industry Using Machine Learning Approach
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Abstract
Machine learning techniques' effectiveness and practicality in manufacturing, particularly servicing, have greatly evolved in recent years. Big Data has important possibilities & prospects for SMEs. Big Data can foster collaboration among SMEs by developing quick fixes for problems across all sectors. By availing use of the availability for judgement, this may be accomplished. For two major reasons, SMEs are carefully chosen inside context: SMEs have the benefit & adaptability for speedier adapting to shifts toward productivity because of the overall assessment with in sector, which causes a little alteration in them to impact bigger macro scale effects. Nevertheless, there are also several problematic concerns in the Big Data setting, including storing, the capacity of the businesses to analyse and produce useful info from all of this, and privacy and confidentiality. Their use allows predictive maintenance, which yields substantial efficiency gains. However, putting such solutions into practise successfully still needs a lot of work in data preparation to get the proper information and interdisciplinarity in teams. Here, small and medium-sized businesses (SME) frequently lack capacity, skill, and experience. The installation of machine learning solutions for predictive maintenance in SME is presented in this study as a methodical and practice-oriented strategy that has previously been proven.
Publication details
- DOI
- 10.1109/ic3i59117.2023.10397688
- OpenAlex
- W4391249519
- Document type
- conference-paper
- Language
- EN
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