A systematic review on big data applications and scope for industrial processing and healthcare sectors

Journal of Big Data

Methodology

Kumar Rahul¹  Rohitash Kumar Banyal²  Neeraj Arora³ 

[1] Department of Basic and Applied Science, NIFTEM, 131028, Sonipat, India;Department of Computer Science and Engineering, Rajasthan Technical University, 324010, Kota, India;School of Science and Technology, Vardhman Mahaveer Open University, 324010, Kota, India;

关键词: Big data;    Data cleaning;    Outliers;    Industrial processing;    Healthcare;   

DOI  :  10.1186/s40537-023-00808-2

 received in 2022-07-06, accepted in 2023-08-02,  发布年份 2023

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY   
© Springer Nature Switzerland AG 2023

【 图 表 】

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