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Big data: survey, technologies, opportunities, and challenges.

Nawsher Khan1, Ibrar Yaqoob2, Ibrahim Abaker Targio Hashem2

  • 1Mobile Cloud Computing Research Lab, Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia ; Department of Computer Science, Abdul Wali Khan University Mardan, Mardan 23200, Pakistan.

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This summary is machine-generated.

Big Data, characterized by rapid growth and diverse challenges, is explored in this study. We classify its attributes and propose a data lifecycle to guide future research and optimal Big Data techniques.

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Area of Science:

  • Computer Science
  • Information Science
  • Data Science

Background:

  • The digital era generates vast amounts of data at unprecedented rates, driven by increasing internet and mobile device connectivity.
  • Exponential data growth presents significant challenges in transfer speed, diversity, management, and security.
  • Despite its growing importance, a comprehensive review of Big Data's fundamental aspects remains limited.

Purpose of the Study:

  • To provide a comprehensive survey and classification of Big Data attributes.
  • To propose a data lifecycle model tailored for Big Data technologies and terminologies.
  • To identify future research directions and open issues in the Big Data domain.

Main Methods:

  • Literature review and synthesis of existing Big Data research.
  • Classification of Big Data characteristics including nature, volume, velocity, and variety.
  • Development of a conceptual data lifecycle model for Big Data.

Main Results:

  • A structured overview of Big Data's key attributes and challenges.
  • A proposed data lifecycle model encompassing Big Data management and analysis.
  • Identification of critical research gaps and future opportunities in Big Data.

Conclusions:

  • Big Data requires systematic approaches for effective management and analysis.
  • Further research is essential to develop advanced techniques for handling Big Data challenges.
  • The proposed data lifecycle offers a framework for understanding and navigating the Big Data landscape.