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Cognitive Computing Meets Big Data: a Paradigm Shift in Analytics

EasyChair Preprint no. 11891

8 pagesDate: January 29, 2024


The convergence of cognitive computing and big data represents a transformative paradigm shift in the field of analytics. This fusion of advanced cognitive technologies with vast and complex datasets heralds a new era in data-driven decision-making and problem-solving. In this paradigm, cognitive computing systems leverage artificial intelligence, machine learning, and natural language processing to comprehend, reason, and learn from the immense volume and variety of data. The abstract explores how this synergy between cognitive computing and big data is redefining traditional analytics approaches. It delves into the capabilities of cognitive systems to autonomously analyze and interpret unstructured data, providing insights that were previously elusive. The abstract also emphasizes the scalability and adaptability of these systems, making them well-suited for handling the velocity, volume, and variety of big data. It addresses the challenges and opportunities presented by the integration of cognitive computing with big data, emphasizing the need for organizations to develop new strategies and skill sets to harness the full potential of this transformative alliance. It sets the stage for a comprehensive exploration of the paper's findings and insights into the practical applications, challenges, and future directions of this emerging paradigm in analytics.

Keyphrases: Big Data, Cognitive Computing, paradigm shift

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Lee Kasowaki and Jones Zavier},
  title = {Cognitive Computing Meets Big Data: a Paradigm Shift in Analytics},
  howpublished = {EasyChair Preprint no. 11891},

  year = {EasyChair, 2024}}
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