Revolutionizing Big Data: AI Algorithms and Predictive Analytics

EasyChair Preprint 11685

Abstract

In the era of information explosion, the proliferation of data has become unprecedented, presenting both immense opportunities and challenges. This paper delves into the realm of big data revolution and explores the pivotal role of artificial intelligence (AI) algorithms in predictive analytics. With the exponential growth of data sources, traditional methods of data processing and analysis have become insufficient to extract meaningful insights efficiently. As a solution, AI-driven algorithms have emerged as powerful tools capable of handling vast datasets and deriving actionable intelligence. This paper begins by elucidating the essence of big data, highlighting its characteristics, sources, and the challenges associated with its analysis. It then investigates the transformative potential of AI algorithms, encompassing machine learning, deep learning, natural language processing, and other AI-driven techniques. These algorithms enable the extraction of patterns, trends, and correlations from colossal datasets, empowering organizations to make informed decisions and predictions. Moreover, the paper examines the application domains where AI algorithms have revolutionized predictive analytics, including but not limited to healthcare, finance, marketing, and cybersecurity. Case studies and real-world examples will be provided to illustrate the tangible impact of AI-driven predictive analytics in these sectors. The paper will also shed light on the future prospects and potential advancements in AI algorithms, envisioning their role in shaping the future of big data analytics.

Keyphrases: Advanced Algorithms, Artificial Intelligence, machine learning

@booklet{EasyChair:11685,
  author    = {Lee Kasowaki and Berkan Deniz},
  title     = {Revolutionizing Big Data: AI Algorithms and Predictive Analytics},
  howpublished = {EasyChair Preprint 11685},
  year      = {EasyChair, 2024}}