000			04485nam a22002897a 4500
003			CUTN
005			20221109132046.0
008			221109b |||||||| |||| 00| 0 eng d
020			_a9781032008110
020			_a9781032191799
020			_a9781003175889
041			_aEnglish
082			_223 _a658.4038028563 _bKAL
100			_aKaliraj, P.
245			_aBig Data Applications in Industry 4.0 / _cEdited by P. Kaliraj and T.Devi.
250			_a1st ed.
260			_aBoca Raton, Florida : _bCRC Press, Taylor & Francis Group, _c2022.
300			_axxiv, 421 p. : _bill. ; _c24 cm.
505			_t1. Data Science and Its Applications Paul Abaraham and Lakshminarayanan _t2. Data, Data IntegrationPavan Gundarapu _t3. Forecasting Principles and Models : An Overview R. Vijayaraghavan _t4. Breaking Technology Barriers in Diabetes and Industry 4.0 Krishnan Swaminathan, Thavamani, and D Palaniswami _t5. Role of Big Data Analytics in Industrial Revolution 4.0 V. Bhuvaneswari _t6. Big Data Infrastructure and Analytics for Education 4.0 Chandra Eswaran and Dr Rathinaraja Jayaraj _t7. Text Analytics in Big Data Environment R.Janani and S. Vijayarani _t8. Business Data Analytics: Application and Research trends S. Sharmila and S. Vijayarani _t9. Role of Big Data Analytics in Financial Service Sector V. Ramanujam and D. Napoleon _t10. Role of Big Data Analytics in Education Domain C. Sivamathi and S. Vijayarani _t11. Machine and Deep Learning Algorithms for Social Media Analytics E.Suganya and S.Vijayarani _t12. Robust Statistics: Methods and Applications Muthukrishnan R. _t13. Big Data in Tribal Healthcare and Biomedical Research Dhivya Venkatesan, Abilash Valsala Gopalakrishnan, Narayanasamy Arul, Chhakchhuak Lalchhandama, Nachimuthu Senthil Kumar, and Balachandar Vellingiri _t14. PySpark towards Data Analytics J. Ramsingh _t15. How to Implement a Data Lake for Large Enterprises? Mr. Ragavendran Chandrasekaran _t16. A Novel Application of Data Mining Techniques for Satellite Performance Analysis S.A.Kannan and T.Devi _t17. Big Data Analytics: A Text Mining Perspective and Applications in Biomedicine and Healthcare Jeyakumar Natarajan, Balu Bhasuran, and Gurusamy Murugesan
520			_aIndustry 4.0 is the latest technological innovation in manufacturing with the goal to increase productivity in a flexible and efficient manner. Changing the way in which manufacturers operate, this revolutionary transformation is powered by various technology advances including artificial intelligence (AI), Big Data analytics, Internet-of-Things (IoT) and cloud computing. Big Data analytics has been identified as one of the significant components of Industry 4.0, as it provides valuable insights for smart factory management. Big Data and Industry 4.0 have the potential to reduce resource consumption and optimize processes, thereby playing a key role in achieving sustainable development. Big Data Applications in Industry 4.0 covers the recent advancements that have emerged in the field of Big Data and its applications. The book introduces the concepts and advanced tools and technologies for representing and processing Big Data. It also covers applications of Big Data in such domains as financial services, education, healthcare, biomedical research, logistics, and warehouse management. Researchers, students, scientists, engineers, and statisticians can turn to this book to learn about concepts, technologies, and applications that solve real world problems. The books features: An introduction to data science and the types of data analytics methods accessible today: An overview of data integration concepts, methodologies, and solutions. A general framework of forecasting principles and applications as well as basic forecasting models including naïve, moving average, and exponential smoothing models. A detailed roadmap of the Big Data evolution and its related technological transformation in computing, along with a brief description of related terminologies. The application of Industry 4.0 and Big Data in the field of education. The features, prospects, and significant role of Big Data in banking industry, as well as various use cases of Big Data in banking, finance services, and insurance. Implementing a Data Lake (DL) in the cloud and the significance of a data lake in for decision-making
650			_aBig Data.
650			_aAnalytics.
650			_aIndustry 4.0.
690			_aGratis
700			_aDevi, T.
942			_2ddc _cBOOKS
999			_c38262 _d38262