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Artificial Intelligence in Big Data: Transforming Insights Through Advanced Algorithms

EasyChair Preprint no. 11684

7 pagesDate: January 4, 2024


The convergence of Artificial Intelligence (AI) and Big Data has led to a transformative paradigm shift in data analysis and insights generation. This paper explores the symbiotic relationship between AI and Big Data, elucidating how advanced algorithms within AI frameworks have revolutionized the extraction, processing, and interpretation of voluminous and complex datasets. The exponential growth of data in various forms – structured, unstructured, and semi-structured – presents challenges and opportunities. AI-powered techniques, including machine learning, deep learning, natural language processing, and predictive analytics, harness the potential of Big Data by discerning patterns, correlations, and hidden insights that elude conventional analytical approaches. This paper delves into the fundamental role of AI in Big Data, elucidating its significance in enhancing decision-making processes across diverse industries. Furthermore, it examines the ethical considerations and potential societal impacts arising from the amalgamation of AI and Big Data, addressing concerns surrounding privacy, bias, and the responsible use of data-driven technologies.

Keyphrases: Advanced Algorithms, Artificial Intelligence, Big Data

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Lee Kasowaki and Ahmed Ozan},
  title = {Artificial Intelligence in Big Data: Transforming Insights Through Advanced Algorithms},
  howpublished = {EasyChair Preprint no. 11684},

  year = {EasyChair, 2024}}
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