Abstract
The rapid observed increase in using the Internet led to the presence of huge amounts of data. Traditional data technologies, techniques, and even applications cannot cope with the new data’s volume, structure, and types of styles. Big data concepts come to assimilate this non-stop flooding. Big data analysis process used to jewel the useful data and exclude the other one which provides better results with minimum resource utilization, time, and cost. Feature selection principle is a traditional data dimension reduction technique, and big data analytics provided modern technologies and frameworks that feature selection can be integrated with them to provide better performance for the principle itself and help in preprocessing of big data on the other hand. The main objective of this paper is to survey the most recent research challenges for big data analysis and preprocessing processes. The analysis is carried out via acquiring data from resources, storing them, then filtered to pick up the useful ones and dismissing the unwanted ones then extracting information. Before analyzing data, it needs preparation to remove noise, fix incomplete data and put it in a suitable pattern. This is done in the preprocessing step by various models like data reduction, cleaning, normalization, preparation, integration, and transformation.
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Ishikiriyama, C.S., Gomes, C.F.S.: Big data: a global overview. In: Emrouznejad, A., Charles, V. (eds.) Big Data for the Greater Good, pp. 35–50. Springer International Publishing, Cham (2019)
Kaisler, S., Armour, F., Espinosa, J.A., Money, W.: Big data: issues and challenges moving forward. In: Proceedings Annual Hawaii International Conference on System Sciences, pp. 995–1004 (2013)
García, S., Ramírez-Gallego, S., Luengo, J., Benítez, J.M., Herrera, F.: Big data preprocessing: methods and prospects. Big Data Anal. 1(1), 1–22 (2016)
Oussous, A., Benjelloun, F.-Z., Lahcen, A.A., Belfkih, S.: Big data technologies: a survey. J. King Saud Univ. Comput. Inf. Sci. 30(4), 431–448 (2018)
Burmester, G., Ma, H., Steinmetz, D., Hartmannn, S.: Big data and data analytics in aviation. In: Durak, U., Becker, J., Hartmann, S., Voros, N. (eds.) Advances in Aeronautical Informatics. Springer International Publishing, Cham (2018)
Amini, S., Gerostathopoulos, I., Prehofer, C.: Big data analytics architecture for real-time traffic control. In: 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems MT-ITS 2017, pp. 710–715 (2017). Tum Llcm
Hashem, I.A.T., Yaqoob, I., Anuar, N.B., Mokhtar, S., Gani, A., Ullah Khan, S.: The rise of big data on cloud computing: review and open research issues. Inf. Syst. 47, 98–115 (2015)
Raghupathi, W., Raghupathi, V.: Big data analytics in healthcare: promise and potential. Heal. Inf. Sci. Syst. 2, 3 (2014)
Ramírez-Gallego, S., Krawczyk, B., García, S., Woźniak, M., Herrera, F.: A survey on data preprocessing for data stream mining: current status and future directions. Neurocomputing 239, 39–57 (2017)
Chen, M., Mao, S., Zhang, Y., Leung, V.C.M
Addo-Tenkorang, R., Helo, P.T.: Big data applications in operations/supply-chain management: a literature review. Comput. Ind. Eng. 101, 528–543 (2016)
Miller, K.W., Michael, K.: Big data: new opportunities and new challenges [guest editors’ introduction]. Computer 46(6), 22–24 (2013)
Muthulakshmi, P., Udhayapriya, S.: A survey on big data issues and challenges. Int. J. Comput. Sci. Eng. 6(6), 1238–1244 (2018)
Huda, M., et al.: Big data emerging technology: insights into innovative environment for online learning resources. Int. J. Emerg. Technol. Learn. 13(1), 23–36 (2018)
Aggarwal, V.B., Bhatnagar, V., Mishra, D.K.: Big Data Analytics. Advances in Intelligent Systems and Computing, vol. 654. Springer, Cham (2015)
Maxwell, S.E., Kelley, K., Rausch, J.R.: Sample size planning for statistical power and accuracy in parameter estimation. Annu. Rev. Psychol. 59, 537–563 (2008)
Sivarajah, U., Kamal, M.M., Irani, Z., Weerakkody, V.: Critical analysis of big data challenges and analytical methods. J. Bus. Res. 70, 263–286 (2017)
Ramannavar, M., Sidnal, N.S.: A proposed contextual model for big data analysis using advanced analytics. Adv. Intell. Syst. Comput. 654, 329–339 (2018)
Vashisht, P., Gupta, V.: Big data analytics techniques: a survey. In: Proceedings 2015 International Conference Green Computing and Internet Things, ICGCIoT 2015, pp. 264–269 (2016)
Gandomi, A., Haider, M.: Beyond the hype: big data concepts, methods, and analytics. Int. J. Inf. Manage. 35(2), 137–144 (2015)
Wang, Y., Kung, L.A., Byrd, T.A.: Big data analytics: understanding its capabilities and potential benefits for healthcare organizations. Technol. Forecast. Soc. Change 126, 3–13 (2018)
Dumka, A., Sah, A.: Smart ambulance system using concept of big data and internet of things. In: Dey, N., Ashour, A.S., Bhatt, C., Fong, S.J. (eds.) Healthcare Data Analytics and Management. Elsevier Inc., Amsterdam (2018)
Tiwari, S., Wee, H.M., Daryanto, Y.: Big data analytics in supply chain management between 2010 and 2016: insights to industries. Comput. Ind. Eng. 115, 319–330 (2018)
Kumar, U., Gambhir, S.: Mobile agent based mapreduce framework for big data processing. Adv. Intell. Syst. Comput. 654, 391–402 (2018)
Taneja, R., Gaur, D.: Robust fuzzy Neuro system for big data analytics. Adv. Intell. Syst. Comput. 654, 543–552 (2018)
Ahmed, Z., Liang, B.T.: Systematically dealing practical issues associated to healthcare data analytics, vol. 70, pp. 599–613. Springer International Publishing (2020)
Praveena, A., Bharathi, B.: A survey paper on big data analytics. In: 2017 International Conference on Information Communication and Embedded Systems ICICES 2017 (2017)
Singh, D., Reddy, C.K.: A survey on platforms for big data analytics. J. Big Data 2(1), 1–20 (2015)
Fu, C., Wang, X., Zhang, L., Qiao, L.: Mining algorithm for association rules in big data based on Hadoop. In: AIP Conference Proceedings, vol. 1955 (2018)
Abdel-Hamid, N.B., ElGhamrawy, S., El Desouky, A., Arafat, H.: A dynamic spark-based classification framework for imbalanced big data. J. Grid Comput. 16(4), 607–626 (2018)
Alcalde-Barros, A., García-Gil, D., García, S., Herrera, F.: DPASF: a flink library for streaming data preprocessing (2018)
Furht, B., Villanustre, F.: Big Data Technologies and Applications, vol. 2, no. 21. Springer, Cham (2016)
García, S., Luengo, J., Herrera, F.: Data preparation basic models. In: Data Preprocessing in Data Mining. Intelligent Systems Reference Library, vol. 72. Springer, Cham (2015)
Russom, P.: Big data analytics - TDWI best practices report. Introduction to Big Data Analytics. TDWI Research, vol. 1, pp. 3–5 (2011)
Di Martino, B., Aversa, R., Cretella, G., Esposito, A., Kołodziej, J.: Big data (lost) in the cloud. Int. J. Big Data Intell. 1(1/2), 3 (2014)
ur Rehman, M.H., Liew, C.S., Abbas, A., Jayaraman, P.P., Wah, T.Y., Khan, S.U.: Big data reduction methods: a survey. Data Sci. Eng. 1(4), 265–284 (2016)
Zhang, W., He, B., Chen, Y., Zhang, Q.: GMR: graph-compatible mapreduce programming model. Multimed. Tools Appl. 78(1), 457–475 (2019)
Ramírez-Gallego, S., Fernández, A., García, S., Chen, M., Herrera, F.: Big data: tutorial and guidelines on information and process fusion for analytics algorithms with MapReduce. Inf. Fusion 42, 51–61 (2018)
Chang, Y.S., Lin, K.M., Tsai, Y.T., Zeng, Y.R., Hung, C.X.: Big data platform for air quality analysis and prediction. In: 2018 27th Wireless Optical Communication Conference WOCC 2018, pp. 1–3 (2018)
Zhao, L., Chen, Z., Hu, Y., Min, G., Jiang, Z.: Distributed feature selection for efficient economic big data analysis. IEEE Trans. Big Data 4(2), 164–176 (2016)
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Shehab, N., Badawy, M., Arafat, H. (2020). Big Data Analytics Concepts, Technologies Challenges, and Opportunities. In: Hassanien, A., Shaalan, K., Tolba, M. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019. AISI 2019. Advances in Intelligent Systems and Computing, vol 1058. Springer, Cham. https://doi.org/10.1007/978-3-030-31129-2_9
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