Big Data Analytics Using Data Mining Techniques: A Survey

  • Shweta MittalEmail author
  • Om Prakash Sangwan
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 955)


Data collected now-a-days is quite huge in size. Also in the future, data will continue to grow at a much higher rate. The survey highlights the basic concepts of big data analytics and its application in the domain of weather prediction. More the data available to us, more accurate will be the results. Relatively small change in the accuracy of models benefits a lot to society. Huge number of statistical and predictive models for weather prediction exists in the literature but the methods are too time consuming and cannot handle unstructured as well as huge datasets. To overcome this problem, various authors have explored the Apache Hadoop Map Reduce framework for processing and storing Big Data. In this paper, we have discussed and analysed the work done by various researchers on weather prediction using big data analytics.


Big data Big data analytics Weather prediction Data mining Hadoop 


  1. 1.
    Evert, F., Fountas, S., Jakovetic, D., Cnnojevic, V., Travlos, I., Kempenaar, C.: Big data for weed control and crop protection. In: Big Data for Weed Control and Crop Protection. Weed Research (2017).
  2. 2.
    Assuncao, M., Calheiros, R., Bianchi, S., Netto, M., Buyya, R.: Big data computing and clouds: trends and future directions. J. Parallel Distrib. Comput. 79–80, 3–15 (2015). Scholar
  3. 3.
  4. 4.
    Giacalone, M., Cusatelli, C., Santarcangelo, V.: Big data compliance for innovative clinical models. Big Data Res. 12, 35–40 (2018). Scholar
  5. 5.
    Dang, Z., Zhu, X., Cheng, D., Zong, M., Zhang, S.: Efficient KNN classification algorithm for big data. J. Neurocomput. 195, 143–148 (2016). Scholar
  6. 6.
    Zhao, W., Ma, H., He, Q.: Parallel K-Means clustering based on MapReduce. In: Jaatun, M.G., Zhao, G., Rong, C. (eds.) CloudCom 2009. LNCS, vol. 5931, pp. 674–679. Springer, Heidelberg (2009). Scholar
  7. 7.
    Maillo, J., Triguero, I., Herrera, F.: A MapReduce-based k-Nearest neighbor approach for big data classification. In: IEEE Trustcom/BigDataSE/ISPA (2015).
  8. 8.
    Tsai, C., Lai, C., Chao, H., Vasilakos, A.: Big data analytics: a survey. J. Big Data 2, 21 (2015). Scholar
  9. 9.
    Majumdar, J., Naraseeyappa, S., Ankalaki, S.: Analysis of agriculture data using data mining techniques: application of big data. Open J. Big Data 4, 20 (2017). Scholar
  10. 10.
    Fan, W., Chong, C., Xiaoling, G., Hua, Y.: Prediction of crop yield using big data. In: 8th International Symposium on Computational Intelligence and Design. IEEE (2015).
  11. 11.
    Bendre, M.R., Thool, R.C., Thool, V.R.: Big data in precision agriculture: weather forecasting for future farming. In: 1st International Conference on Next Generation Computing Technologies. IEEE (2015).
  12. 12.
    Sneha, N., Majumdar, J.: Big data application in agriculture to maximize the rice yield crop production using data mining techniques. Int. J. Innov. Res. Comput. Commun. Eng. (2017).
  13. 13.
    Kushwaha, A., Bhattachrya, S.: Crop yield prediction using agro algorithm in hadoop. Int. J. Comput. Sci. Inf. Technol. Secur. (IJCSITS) 5(2), 271–274 (2015)Google Scholar
  14. 14.
    Nguyen, V., Nguyen, S., Kim, K.: Design of a platform for collecting and analyzing agricultural big data. J. Digit. Contents Soc. 18(1), 149–158 (2017). Scholar
  15. 15.
    Reddy, P., Babu, A.: Survey on weather prediction using big data analystics. In: Second International Conference on Electrical, Computer and Communication Technologies. IEEE (2017).
  16. 16.
    Shobha, N., Asha, T.: Monitoring weather based meteorological data: clustering approach for analysis. In: International Conference on Innovative Mechanisms for Industry Applications. IEEE (2017).
  17. 17.
    Nikam, V., Meshram, B.: Modeling rainfall prediction using data mining method. In: Fifth International Conference on Computational Intelligence, Modelling and Simulation. IEEE (2013).
  18. 18.
    Tsagalidis, E., Evangelidis, G.: The effect of training set selection in meteorological data mining. In: Fourteenth Panhellenic Conference on Informatics. IEEE (2010).
  19. 19.
    Navadia, S., Yadav, P., Thomas, J., Shaikh, S.: Weather prediction: a novel approach for measuring and analyzing weather data. In: International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud). IEEE (2017).
  20. 20.
    Anchalia, P., Roy, K.: The k-Nearest neighbor algorithm using map reduce paradigm. In: Fifth International Conference on Intelligent Systems, Modelling and Simulation. IEEE (2014).
  21. 21.
    Fang, W., Sheng, V.S., Wen, X., Pan, W.: Meteorological data analysis using MapReduce. Sci. World J. (2014).
  22. 22.
    Ismail, K., Majid, M., Zain, J., Abu Bakar, N.: Big data prediction framework for weather temperature based on MapReduce algorithm. In: Conference on Open Systems. IEEE (2016).
  23. 23.
    Riyaz, P.A., Varghese, S.: Leveraging map reduce with hadoop for weather data analytics. IOSR J. Comput. Eng. 17(3), 6–12 (2015). Scholar
  24. 24.
    Mazhar, A., Ikram, M.T., Butt, N.A., Butt, A.J.: Do we really have to consider data mining techniques for meteorological data. In: Fourth International Conference on Aerospace Science and Engineering. IEEE (2015).
  25. 25.
    Marjani, M., et al.: Big IoT data analytics: architecture, opportunities, and open research challenges. IEEE Access 5, 5247–5261 (2017). Scholar
  26. 26.
    Alves, G.M., Cruvinel, P.E.: Big data environment for agricultural soil analysis from CT digital images. In: Tenth International Conference on Semantic Computing. IEEE (2016).
  27. 27.
    Mohapatra, S., Upadhyay, A., Gola, C.: Rainfall prediction based on 100 years of meteorological data. In: International Conference on Computing and Communication Technologies for Smart Nation. IEEE (2017).
  28. 28.
    Pandey, A., Agrawal, C., Agrawal, M.: A Hadoop based weather prediction model for classification of weather data. In: Second International Conference on Electrical, Computer and Communication Technologies (ICECCT). IEEE (2017).
  29. 29.
    Kumar, M., Nagar, M.: Big data analytics in agriculture and distribution channel. In: Proceedings of the IEEE, International Conference on Computing Methodologies and Communication (2017).

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Guru Jambeshwar University of Science and TechnologyHisarIndia

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