Navigating the Confluence: Big Data Analytics and Artificial Intelligence - Innovations, Challenges, and Future Directions

EasyChair Preprint 12052

Abstract

This paper delves into the dynamic intersection of Big Data Analytics and Artificial Intelligence, exploring the synergies, innovations, challenges, and future directions within this transformative landscape. In an era where data has become the lifeblood of technological advancements, the integration of advanced analytics and AI technologies holds immense promise for revolutionizing decision-making processes across various domains. The paper critically examines the innovative applications arising from the confluence of Big Data Analytics and Artificial Intelligence, shedding light on how organizations can harness the power of vast datasets to drive insightful and intelligent decision-making. Key innovations discussed include advanced machine learning algorithms, predictive analytics, and deep learning techniques, which enable the extraction of meaningful patterns and insights from massive datasets. The challenges encountered in this convergence, such as data privacy concerns, ethical considerations, and the need for scalable infrastructure, are also thoroughly addressed. Moreover, the paper provides a forward-looking perspective on the future directions of this amalgamation, envisioning the evolution of data-driven decision-making in the wake of ongoing technological advancements

Keyphrases: Artificial Intelligence, Big Data Analytics, Challenges, Ethical Considerations, Future directions, Predictive Analytics, Technological Advancements, convergence, data privacy, decision making, deep learning, innovations, machine learning

@booklet{EasyChair:12052,
  author    = {Jonny Bairstow},
  title     = {Navigating the Confluence: Big Data Analytics and Artificial Intelligence - Innovations, Challenges, and Future Directions},
  howpublished = {EasyChair Preprint 12052},
  year      = {EasyChair, 2024}}