Big Data Analytics, Processing Models, Taxonomy of Tools, V's, and Challenges: State-of-Art Review and Future Implications

被引:0
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作者
Dasari S. [1 ]
Kaluri R. [1 ]
机构
[1] School of Information Technology and Engineering, Vellore Institute of Technology, Vellore
关键词
All Open Access; Gold;
D O I
10.1155/2023/3976302
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学科分类号
摘要
In the current digital era, data is budding tremendously from various sources like banks, businesses, education, entertainment, etc. Due to its significant consequence, it became a prominent proceeding for numerous research areas like the semantic web, machine learning, computational intelligence, and data mining. For knowledge extraction, several corporate sectors depend on tweets, blogs, and social data to get adequate analysis. It helps them predict the customer's tastes and preferences, optimize the usage of resources. In some cases, the same data creates complications that lead to a problem named as big data. To solve this, so many researchers have given various solutions. Based on literature analysis formulated 6-s simulation towards big data, detailed information about characteristics, a taxonomy of tools, and discussed various processing paradigms. No one tool can truly fit for all solutions, so this paper helps to make decisions smoothly by providing enough information and discussing major privacy issues and future directions. © 2023 Sandeep Dasari and Rajesh Kaluri.
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  • [1] Big Data in Cardiology: State-of-Art and Future Prospects
    Dai, Haijiang
    Younis, Arwa
    Kong, Jude Dzevela
    Puce, Luca
    Jabbour, Georges
    Yuan, Hong
    Bragazzi, Nicola Luigi
    [J]. FRONTIERS IN CARDIOVASCULAR MEDICINE, 2022, 9
  • [2] The state of the art and taxonomy of big data analytics: view from new big data framework
    Azlinah Mohamed
    Maryam Khanian Najafabadi
    Yap Bee Wah
    Ezzatul Akmal Kamaru Zaman
    Ruhaila Maskat
    [J]. Artificial Intelligence Review, 2020, 53 : 989 - 1037
  • [3] The state of the art and taxonomy of big data analytics: view from new big data framework
    Mohamed, Azlinah
    Najafabadi, Maryam Khanian
    Wah, Yap Bee
    Zaman, Ezzatul Akmal Kamaru
    Maskat, Ruhaila
    [J]. ARTIFICIAL INTELLIGENCE REVIEW, 2020, 53 (02) : 989 - 1037
  • [4] Continuous improvement approach: state-of-art review and future implications
    Singh, Jagdeep
    Singh, Harwinder
    [J]. INTERNATIONAL JOURNAL OF LEAN SIX SIGMA, 2012, 3 (02) : 88 - 111
  • [5] Next-Generation Big Data Analytics: State of the Art, Challenges, and Future Research Topics
    Lv, Zhihan
    Song, Houbing
    Basanta-Val, Pablo
    Steed, Anthony
    Jo, Minho
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 13 (04) : 1891 - 1899
  • [6] Big data analytics in smart grids: state-of-the-art, challenges, opportunities, and future directions
    Bhattarai, Bishnu P.
    Paudyal, Sumit
    Luo, Yusheng
    Mohanpurkar, Manish
    Cheung, Kwok
    Tonkoski, Reinaldo
    Hovsapian, Rob
    Myers, Kurt S.
    Zhang, Rui
    Zhao, Power
    Manic, Milos
    Zhang, Song
    Zhang, Xiaping
    [J]. IET SMART GRID, 2019, 2 (02) : 141 - 154
  • [7] A Review of Artificial Intelligence to Enhance the Security of Big Data Systems: State-of-Art, Methodologies, Applications, and Challenges
    Dai, Duan
    Boroomand, Sahar
    [J]. ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2022, 29 (02) : 1291 - 1309
  • [8] A Review of Artificial Intelligence to Enhance the Security of Big Data Systems: State-of-Art, Methodologies, Applications, and Challenges
    Duan Dai
    Sahar Boroomand
    [J]. Archives of Computational Methods in Engineering, 2022, 29 : 1291 - 1309
  • [9] Big Data Machine Learning and Graph Analytics: Current State and Future Challenges
    Huang, H. Howie
    Liu, Hang
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2014,
  • [10] Values, challenges and future directions of big data analytics in healthcare: A systematic review
    Galetsi, P.
    Katsaliaki, K.
    Kumar, S.
    [J]. SOCIAL SCIENCE & MEDICINE, 2019, 241