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Synergizing AI and Big Data: a Futuristic Approach to Data Management

EasyChair Preprint no. 11889

7 pagesDate: January 29, 2024


In the era of unprecedented data generation, the integration of Artificial Intelligence (AI) and Big Data technologies has emerged as a transformative force in reshaping traditional approaches to data management. This paper explores the synergies between AI and Big Data, envisioning a futuristic approach to data management that harnesses the power of advanced analytics, machine learning, and large-scale data processing. The first section of the paper provides an overview of the current landscape of Big Data and AI, highlighting their strengths and challenges. The second section delves into the potential benefits of synergizing AI and Big Data. Moreover, the integration of AI into Big Data workflows can automate decision-making processes, optimize resource allocation, and drive innovation across various industries. The third section explores key challenges and considerations associated with the integration of AI and Big Data. The fourth section outlines a conceptual framework for the synergistic integration of AI and Big Data. The proposed framework provides a roadmap for navigating the challenges and realizing the full potential of this synergistic approach in the dynamic landscape of data management.

Keyphrases: Artificial Intelligence (AI), Big Data, data management

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Lee Kasowaki and Jackob Kooper},
  title = {Synergizing AI and Big Data: a Futuristic Approach to Data Management},
  howpublished = {EasyChair Preprint no. 11889},

  year = {EasyChair, 2024}}
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