Next-Gen Analytics: AI's Impact on Big Data Strategies

EasyChair Preprint 11892

Abstract

In the rapidly evolving landscape of information technology, the convergence of Artificial Intelligence (AI) and Big Data has ushered in a new era of analytics, transforming the way organizations derive insights from vast and complex datasets. This paper explores the profound impact of AI on Big Data strategies, examining the synergies between advanced analytics techniques and the ever-expanding volume, velocity, and variety of data. The paper begins by providing an overview of the current state of Big Data and AI integration, highlighting the challenges and opportunities posed by the sheer magnitude and diversity of data sources. It delves into the role of AI in enhancing data processing capabilities, predictive modeling, and decision-making processes, thereby revolutionizing traditional approaches to analytics. Furthermore, the paper investigates key AI-powered technologies shaping the next generation of analytics, including machine learning, natural language processing, and deep learning. It explores how these technologies enable organizations to uncover hidden patterns, extract meaningful insights, and make data-driven decisions in real time. The discussion extends to the impact of AI on data governance and privacy considerations. As organizations leverage AI to extract value from data, ethical concerns and regulatory compliance become integral components of Big Data strategies. The paper explores the measures and frameworks that must be adopted to ensure responsible and secure use of AI in the context of Big Data analytics.

Keyphrases: Artificial Intelligence (AI), Big Data Strategies, Next-Gen Analytics

@booklet{EasyChair:11892,
  author    = {Mustafa Zain and Lee Kasowaki},
  title     = {Next-Gen Analytics: AI's Impact on Big Data Strategies},
  howpublished = {EasyChair Preprint 11892},
  year      = {EasyChair, 2024}}