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Introduction to Big Data Analytics

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Towards the Integration of IoT, Cloud and Big Data

Part of the book series: Studies in Big Data ((SBD,volume 137))

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Abstract

Nowadays, social media and networks, scientific instruments, mobile devices, mobile devices, and a high volume of information data (tabular data, text files, images, videos, audio, logos, etc.) is generated at high velocity by social media and networks, scientific instruments, mobile devices, and sensors technology and networks. In these types of data, data quality is usually not guaranteed. This data can be structured or unstructured, necessitating a cost-effective, innovative method of data processing to improve understanding and decision-making. This chapter covers some introduction to Big Data analysis and its need, skills required for Big Data analysis, characteristics of Big data analysis, an overview of the Hadoop ecosystem, and some use cases of Big Data analysis.

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References

  1. Lazer, D., Radford, J.: Data ex machina: introduction to big data. Ann. Rev. Sociol. 43, 19–39 (2017)

    Article  Google Scholar 

  2. Kitchin, R., Lauriault, T.P.: Small data in the era of big data. GeoJournal 80(4), 463–475 (2015)

    Article  Google Scholar 

  3. Fernández, A., del Río, S., Chawla, N.V., Herrera, F.: An insight into imbalanced big data classification: outcomes and challenges. Complex Intell. Syst. 3(2), 105–120 (2017)

    Article  Google Scholar 

  4. G’eczy, P.: Big data characteristics. Macro Theme Rev. 3(6), 94–104 (2014)

    Google Scholar 

  5. Ansari, S., Mohanlal, R., Poncela, J., Ansari, A., Mohanlal, K.: Importance of big data. In: Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence, pp. 1–19. IGI Global (2015)

    Google Scholar 

  6. Fan, J., Han, F., Liu, H.: Challenges of big data analysis. Natl. Sci. Rev. 1(2), 293–314 (2014)

    Article  Google Scholar 

  7. Al Nuaimi, E., Al Neyadi, H., Mohamed, N., Al-Jaroodi, J.: Applications of big data to smart cities. J. Internet Serv. Appl. 6(1), 1–15 (2015)

    Article  Google Scholar 

  8. Aloysius, J.A., Hoehle, H., Goodarzi, S., Venkatesh, V.: Big data initiatives in retail environments: linking service process perceptions to shopping outcomes. Ann. Oper. Res. 270(1), 25–51 (2018)

    Article  Google Scholar 

  9. Verma, J.P., Patel, B., Patel, A.: Big data analysis: recommendation system with hadoop framework. In: 2015 IEEE International Conference on Computational Intelligence & Communication Technology, pp. 92–97. IEEE (2015)

    Google Scholar 

  10. Rizwan, P., Suresh, K., Babu, M.R.: Real-time smart traffic management system for smart cities by using Internet of things and big data. In: 2016 International Conference on Emerging Technological Trends (ICETT), pp. 1–7. IEEE (2016)

    Google Scholar 

  11. Fathi, F., Abghour, N., Ouzzif, M.: From big data to better behavior in self-driving cars. In: Proceedings of the 2018 2nd International Conference on Cloud and Big Data Computing, pp. 42–46 (2018)

    Google Scholar 

  12. Daniel, B.K.: Big data in higher education: the big picture. In: Big Data and Learning Analytics in Higher Education, pp. 19–28. Springer (2017)

    Google Scholar 

  13. Mahapatra, S., Singh, A.: Application of IoT-based smart devices in health care using fog computing. In: Fog Data Analytics for IoT Applications, pp. 263–278. Springer (2020).

    Google Scholar 

  14. Singh, A., Mahapatra, S.: Network-based applications of multimedia big data computing in iot environment. In: Multimedia Big Data Computing for IoT Applications, pp. 435–452. Springer (2020).

    Google Scholar 

  15. Kannan, S., Karuppusamy, S., Nedunchezhian, A., Venkateshan, P., Wang, P., Bojja, N., Kejariwal, A.: Chapter 3 - Big data analytics for social media. In: Buyya, R., Calheiros, R.N., Dastjerdi, A.V. (eds.) Big Data, pp. 63–94. Morgan Kaufmann (2016).

    Google Scholar 

  16. Tsai, C.W., Lai, C.F., Chao, H.C., Vasilakos, A.V.: Big data analytics: a survey. J. Big Data 2(1), 1–32 (2015)

    Article  Google Scholar 

  17. Landset, S., Khoshgoftaar, T.M., Richter, A.N., Hasanin, T.: A survey of open source tools for machine learning with big data in the hadoop ecosystem. J. Big Data 2(1), 1–36 (2015)

    Article  Google Scholar 

  18. Monteith, J.Y., McGregor, J.D., Ingram, J.E.: Hadoop and its evolving ecosystem. In: 5th International Workshop on Software Ecosystems (IWSECO 2013), vol. 50, p. 74. Citeseer (2013)

    Google Scholar 

  19. Goyal, L., Arora, N.: Deep transfer learning approach for detection of covid-19 from chest x-ray images. Int. J. Comput. Appl. 975, 8887 (2020)

    Google Scholar 

  20. Kakde, A., Sharma, D., Arora, N.: Optimal classification of covid-19: a transfer learning approach. Int. J. Comput. Appl. 176(20), 25–31 (2020)

    Google Scholar 

  21. Datta, G., Joshi, N., Gupta, K.: Empirical analysis of performance of MT systems and its metrics for English to Bengali: a black box-based approach. In: Intelligent Systems, Technologies and Applications, pp. 357–371. Springer (2021)

    Google Scholar 

  22. Sharma, A., Tiwari, S., Arora, N., Sharma, S.C.: Introduction to blockchain. In: Blockchain Applications in IoT Ecosystem, pp. 1–14. Springer (2021)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Electronics and Computer Discipline, Indian Institute of Technology, Roorkee, India

    Nitin Arora

  2. Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, India

    Anupam Singh

  3. Department of Computer Science and Engineering, Indian Institute of Technology, Dharwad, India

    Vivek Shahare

  4. School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India

    Goutam Datta

Authors
  1. Nitin Arora
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  2. Anupam Singh
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  3. Vivek Shahare
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  4. Goutam Datta
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Corresponding author

Correspondence to Nitin Arora .

Editor information

Editors and Affiliations

  1. Department of CSIT, Faculty of Engineering and Technology, M.J.P. Rohilkhand University, Bareilly, India

    Vinay Rishiwal

  2. Glocal University, Saharanpur, Uttar Pradesh, India

    Pramod Kumar

  3. Netaji Subhas University of Technology, New Delhi, India

    Anuradha Tomar

  4. Department of Data Science, University of North Texas, Denton, TX, USA

    Priyan Malarvizhi Kumar

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Arora, N., Singh, A., Shahare, V., Datta, G. (2023). Introduction to Big Data Analytics. In: Rishiwal, V., Kumar, P., Tomar, A., Malarvizhi Kumar, P. (eds) Towards the Integration of IoT, Cloud and Big Data. Studies in Big Data, vol 137. Springer, Singapore. https://doi.org/10.1007/978-981-99-6034-7_1

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