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001 9781003175889
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008 210826s2022 flu ob 001 0 eng
040 _aOCoLC-P
_beng
_erda
_cOCoLC-P
020 _a9781003175889
_q(ebk)
020 _a1003175880
_q(ebk)
020 _z9781032008110
_q(hbk)
020 _z9781032191799
_q(pbk)
020 _a9781000537666
_q(electronic bk. : PDF)
020 _a1000537668
_q(electronic bk. : PDF)
020 _a9781000537673
_q(electronic bk. : EPUB)
020 _a1000537676
_q(electronic bk. : EPUB)
035 _a(OCoLC)1269098841
035 _a(OCoLC-P)1269098841
050 0 0 _aT59.6
072 7 _aCOM
_x021030
_2bisacsh
072 7 _aBUS
_x082000
_2bisacsh
072 7 _aCOM
_x039000
_2bisacsh
072 7 _aUN
_2bicssc
082 0 0 _a658.4/038028563
_223
245 0 0 _aBig data applications in industry 4.0 /
_cedited by P. Kaliraj and Devi Thirupathi.
250 _a1st edition.
264 1 _aBoca Raton, FL :
_bCRC Press,
_c2022.
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
500 _a"An Auerbach book".
520 _a"Industry 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"--
_cProvided by publisher.
505 0 _a1. Data Science and Its ApplicationsPaul Abaraham and Lakshminarayanan2. Data, Data IntegrationPavan Gundarapu3. Forecasting Principles and Models : An Overview R. Vijayaraghavan4. Breaking Technology Barriers in Diabetes and Industry 4.0Krishnan Swaminathan, Thavamani, and D Palaniswami 5. Role of Big Data Analytics in Industrial Revolution 4.0V. Bhuvaneswari6. Big Data Infrastructure and Analytics for Education 4.0Chandra Eswaran and Dr Rathinaraja Jayaraj7. Text Analytics in Big Data EnvironmentR.Janani and S. Vijayarani8. Business Data Analytics: Application and Research trendsS. Sharmila and S. Vijayarani9. Role of Big Data Analytics in Financial Service Sector V. Ramanujam and D. Napoleon10. Role of Big Data Analytics in Education DomainC. Sivamathi and S. Vijayarani11. Machine and Deep Learning Algorithms for Social Media AnalyticsE.Suganya and S.Vijayarani12. Robust Statistics: Methods and ApplicationsMuthukrishnan R.13. Big Data in Tribal Healthcare and Biomedical ResearchDhivya Venkatesan, Abilash Valsala Gopalakrishnan, Narayanasamy Arul, Chhakchhuak Lalchhandama, Nachimuthu Senthil Kumar, and Balachandar Vellingiri 14. PySpark towards Data AnalyticsJ. Ramsingh15. How to Implement a Data Lake for Large Enterprises?Mr. Ragavendran Chandrasekaran16. A Novel Application of Data Mining Techniques for Satellite Performance AnalysisS.A.Kannan and T.Devi 17. Big Data Analytics: A Text Mining Perspective and Applications in Biomedicine and HealthcareJeyakumar Natarajan, Balu Bhasuran, and Gurusamy Murugesan
588 _aOCLC-licensed vendor bibliographic record.
650 0 _aIndustry 4.0.
650 0 _aBig data.
650 7 _aCOMPUTERS / Database Management / Data Mining
_2bisacsh
650 7 _aBUSINESS & ECONOMICS / Industrial Management
_2bisacsh
650 7 _aCOMPUTERS / Management Information Systems
_2bisacsh
700 1 _aKaliraj, P.,
_eeditor.
700 1 _aThirupathi, Devi,
_eeditor.
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9781003175889
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999 _c4968
_d4968