Main Article Content
Abstract
In today's Big Data era, data is generated and collected rapidly, in large volumes, and in various formats from diverse sources. Many governments and private organizations view the Big Data era as an opportunity to compete and thrive. By utilizing Big Data analytic techniques, they have gained valuable knowledge and insights from massive datasets, which they use in decision-making and planning processes. Big Data analytics differs from traditional data analytics due to its volume, variety, and velocity. However, numerous challenges exist in this field. This article explores the fundamental concepts of Big Data analytics, examines its problems and challenges, and proposes suitable solutions to address them.
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References
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References
Katal A, Wazid M, Goudar RH. Big data: Issues, challenges, tools and Good practices. 2013 6th Int Conf Contemp Comput IC3 2013. 2013;404–9.
2Kaisler S, Armour F, Espinosa JA, Money W. Big data: Issues and challenges moving forward. Proc Annu Hawaii Int Conf Syst Sci. 2013;995–1004.
Villars RL, Olofson CW, Eastwood M. Big Data: What It is and Why You Should Care. IDC White Pap [Internet]. 2011;7–8. Available from: http://www.tracemyflows.com/uploads/big_data/IDC_AMD_Big_Data_Whitepaper.pdf
Sujitparapitaya S, Shirani A, Roldan M. Issues in Information Systems. Issues Inf Syst. 2012;13(2):112–22.
Sukumar SR. Open Research Challenges with Big Data - A Data-Scientist ’ s Perspective. 2015;1272–8.
Russom P. BIG DATA ANALYTICS - TDWI BEST PRACTICES REPORT Introduction to Big Data Analytics. TDWI best Pract report, fourth Quart [Internet]. 2011;19(4):1–34. Available from: https://vivomente.com/wp-content/uploads/2016/04/big-data-analytics-white-paper.pdf
Ma C, Zhang HH, Wang X. Machine learning for Big Data analytics in plants. Trends Plant Sci [Internet]. 2014;19(12):798–808. Available from: http://dx.doi.org/10.1016/j.tplants.2014.08.004
Boyd D, Crawford K. Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Inf Commun Soc. 2012;15(5):662–79.
Tsai CW, Lai CF, Chao HC, Vasilakos A V. Big data analytics : a survey. J Big Data. 2015;1–32.
Wang X, Yang LT, Member S, Liu H, Deen MJ. A Big Data-as-a-Service Framework : State-of-the-art and Perspectives. 2017;7790(c):1–17.
Wang X, He Y. Learning from Uncertainty for Big Data. Ieee Syst Man Cybern Mag [Internet]. 2016;(August). Available from: http://www.hebmlc.org/UploadFiles/20161121203535376.pdf
Wozniak JM, Wilde M, Foster IT. Language features for scalable distributed-memory dataflow computing. Proc - 2014 4th Work Data-Flow Exec Model Extrem Scale Comput DFM 2014. 2014;2(Vdl):50–3.