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Books on the topic 'Data engineering and data science'

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Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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1

Cui, Zhen, Jinshan Pan, Shanshan Zhang, Liang Xiao, and Jian Yang, eds. Intelligence Science and Big Data Engineering. Visual Data Engineering. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36189-1.

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2

Lee, Roger, ed. Big Data, Cloud Computing, Data Science & Engineering. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-96803-2.

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3

Lee, Roger, ed. Big Data, Cloud Computing, and Data Science Engineering. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-24405-7.

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4

He, Xiaofei, Xinbo Gao, Yanning Zhang, Zhi-Hua Zhou, Zhi-Yong Liu, Baochuan Fu, Fuyuan Hu, and Zhancheng Zhang, eds. Intelligence Science and Big Data Engineering. Image and Video Data Engineering. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23989-7.

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5

King, Tim. Data Network Engineering. Boston, MA: Springer US, 1999.

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6

Cheremisinoff, Paul N. Process engineering data book. Lancaster, PA: Technomic Pub., 1995.

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7

Unit, Engineering Sciences Data. Engineering sciences data: fatigue - fracture mechanics data. London: Engineering Sciences Data Unit, 1985.

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8

Unit, Engineering Sciences Data. Engineering sciences data: wind engineering. London: Engineering Sciences Data Unit, 1985.

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9

Madarshahian, Ramin, and Francois Hemez, eds. Data Science in Engineering, Volume 9. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-76004-5.

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10

Polkowski, Zdzislaw, Sambit Kumar Mishra, and Julian Vasilev. Data Science in Engineering and Management. New York: CRC Press, 2021. http://dx.doi.org/10.1201/9781003216278.

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11

Madarshahian, Ramin, and Francois Hemez, eds. Data Science in Engineering, Volume 9. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04122-8.

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12

Sun, Yi, Huchuan Lu, Lihe Zhang, Jian Yang, and Hua Huang, eds. Intelligence Science and Big Data Engineering. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67777-4.

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13

Yang, Jian, Fang Fang, and Changyin Sun, eds. Intelligent Science and Intelligent Data Engineering. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36669-7.

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14

Zhang, Yanning, Zhi-Hua Zhou, Changshui Zhang, and Ying Li, eds. Intelligent Science and Intelligent Data Engineering. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31919-8.

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15

Peng, Yuxin, Kai Yu, Jiwen Lu, and Xingpeng Jiang, eds. Intelligence Science and Big Data Engineering. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02698-1.

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16

Sun, Changyin, Fang Fang, Zhi-Hua Zhou, Wankou Yang, and Zhi-Yong Liu, eds. Intelligence Science and Big Data Engineering. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-42057-3.

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17

Unit, Engineering Sciences Data. Engineering sciences data: structures. London: Engineering Sciences Data Unit, 1986.

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18

Unit, Engineering Sciences Data. Engineering sciences data: aerodynamics. London: Engineering Sciences Data Unit, 1989.

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19

Unit, Engineering Sciences Data. Engineering Sciences data: structures. London: Engineering SciencesData Unit, 1991.

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20

Unit, Engineering Sciences Data. Engineering sciences data: dynamics. London: Engineering Sciences Data Unit, 1991.

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21

Cui, Zhen, Jinshan Pan, Shanshan Zhang, Liang Xiao, and Jian Yang, eds. Intelligence Science and Big Data Engineering. Big Data and Machine Learning. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36204-1.

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22

Liu, Qing. Data Provenance and Data Management in eScience. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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23

Stahlbock, Robert, Gary M. Weiss, Mahmoud Abou-Nasr, Cheng-Ying Yang, Hamid R. Arabnia, and Leonidas Deligiannidis, eds. Advances in Data Science and Information Engineering. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71704-9.

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24

Auer, Michael E., and Dominik May, eds. Cross Reality and Data Science in Engineering. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-52575-0.

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25

Unit, Engineering Sciences Data. Engineering Sciences data: heat transfer. London: Engineering Sciences Data Unit, 1985.

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26

Unit, Engineering Sciences Data. Engineering Sciences data: heat transfer. London: Engineering Sciences Data Unit, 1989.

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27

Unit, Engineering Sciences Data. Engineering Sciences data: heat transfer. London: Engineering Sciences Data Unit, 1988.

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28

Unit, Engineering Sciences Data. Engineering sciences data: heat transfer. London: ESDU International, 1986.

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29

Unit, Engineering Sciences Data. Engineering sciences data: heat transfer. London: ESDU International, 1987.

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30

Unit, Engineering Sciences Data. Engineering sciences data: Acoustic fatigue. London: Engineering Sciences Data Unit, 1991.

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31

He, Xiaofei, Xinbo Gao, Yanning Zhang, Zhi-Hua Zhou, Zhi-Yong Liu, Baochuan Fu, Fuyuan Hu, and Zhancheng Zhang, eds. Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23862-3.

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32

Silvester, P. P. Data structures for engineering software. Southampton: Computational Mechanics Publications, 1993.

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33

Institute Of Electrical and Electronics Engineers. Computing in science & engineering. New York, NY: Institute of Electrical and Electronics Engineers, 1999.

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34

Vardeman, Stephen B. Basic engineering data collection and analysis. Pacific Grove, CA: Brooks/Cole, 2001.

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35

John, Talburt, Talley Terry Michael, and SpringerLink (Online service), eds. Data Engineering: Mining, Information and Intelligence. Boston, MA: Springer Science+Business Media, LLC, 2010.

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36

Guida, Giovanni. Software Prototyping in Data and Knowledge Engineering. Dordrecht: Springer Netherlands, 1999.

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37

Dunn, Patrick F. Measurement and data analysis for engineering and science. 2nd ed. Boca Raton: Taylor & Francis, 2010.

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38

Measurement and data analysis for engineering and science. 2nd ed. Boca Raton, FL: CRC Press/Taylor & Francis, 2010.

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39

Measurement and data analysis for engineering and science. Boston: McGraw-Hill Higher Education, 2005.

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40

Mahalle, Parikshit Narendra, Gitanjali Rahul Shinde, Priya Dudhale Pise, and Jyoti Yogesh Deshmukh. Foundations of Data Science for Engineering Problem Solving. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-5160-1.

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41

Sachdeva, Shelly, Yutaka Watanobe, and Subhash Bhalla, eds. Big-Data-Analytics in Astronomy, Science, and Engineering. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96600-3.

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42

Big Data, Cloud Computing, Data Science & Engineering. Springer, 2018.

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43

Big Data, Cloud Computing, Data Science & Engineering. Springer, 2018.

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44

Data Engineering and Data Science: Concepts and Applications. Wiley & Sons, Incorporated, John, 2022.

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45

Kumar, Kukatlapalli Pradeep, Vinay Jha Pillai, Hari Murthy, Aynur Unal, and M. Niranjanamurthy. Data Engineering and Data Science: Concepts and Applications. Wiley & Sons, Incorporated, John, 2023.

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46

Kumar, Kukatlapalli Pradeep, Vinay Jha Pillai, Hari Murthy, Aynur Unal, and M. Niranjanamurthy. Data Engineering and Data Science: Concepts and Applications. Wiley & Sons, Incorporated, John, 2022.

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47

Kumar, Kukatlapalli Pradeep, Vinay Jha Pillai, Hari Murthy, Aynur Unal, and M. Niranjanamurthy. Data Engineering and Data Science: Concepts and Applications. Wiley & Sons, Incorporated, John, 2023.

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48

Big Data, Cloud Computing, and Data Science Engineering. Springer International Publishing AG, 2023.

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49

Lee, Roger. Big Data, Cloud Computing, and Data Science Engineering. Springer, 2019.

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50

Lee, Roger. Big Data, Cloud Computing, and Data Science Engineering. Springer International Publishing AG, 2020.

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