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Abstract
Nowadays, big data is an emerging area of computer science. Data are generated through different sources such as social media, e-commerce, blogs, banking, healthcare, transactions, apps, websites, opinion platforms, etc. It is processed for effective utilization in different industries, including healthcare. These enormous generated data are essential for data analysis and processing for industrial needs. This paper reviews the work of various authors who have contributed to data collection, analyzing, processing, and viewing to explore the importance and possibilities of big data in industrial processing applications and healthcare sectors. It identifies different opportunities and challenges (data cleaning, missing values, and outlier analysis) along with applications and features of big data. This systematic review further proposed dirty data detection and cleaning and outlier detection models that can be used for many applications. The data cleaning and outlier detection models use the optimizations concept to solve the optimal centroid selection problem and suspected data.
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Details
1 NIFTEM, Department of Basic and Applied Science, Sonipat, India (GRID:grid.464625.7) (ISNI:0000 0004 1775 8475)
2 Rajasthan Technical University, Department of Computer Science and Engineering, Kota, India (GRID:grid.449434.a) (ISNI:0000 0004 1800 3365)
3 Vardhman Mahaveer Open University, School of Science and Technology, Kota, India (GRID:grid.445108.c) (ISNI:0000 0004 1767 3690)
