Unleashing the Power of Neural Networks in Big Data Analytics: Harnessing Insights from Data-Driven Approaches

EasyChair Preprint 12482

Abstract

This paper explores the utilization of neural networks in the realm of big data analytics, focusing on how these powerful algorithms can be harnessed to extract valuable insights from vast datasets. By employing data-driven approaches, we delve into the methodologies that enable the effective leveraging of neural networks for enhanced analysis and interpretation of big data. We discuss the inherent capabilities of neural networks to handle complex patterns and relationships within large-scale datasets, facilitating the discovery of actionable insights. Furthermore, we highlight the importance of integrating diverse data sources and implementing robust preprocessing techniques to optimize the performance of neural networks in big data analytics. Through realworld examples and case studies, we demonstrate the potential impact of utilizing neural networks in various domains such as finance, healthcare, and marketing. Ultimately, this paper aims to provide a comprehensive overview of the strategies and best practices for maximizing the potential of neural networks in big data analytics, emphasizing the importance of data-driven decisionmaking in driving business success and innovation.

Keyphrases: Big Data Analytics, Data-driven approaches, Integration, Optimization, Preprocessing, Relationships, complex patterns, insights, neural networks

@booklet{EasyChair:12482,
  author    = {Haney Zaki},
  title     = {Unleashing the Power of Neural Networks in Big Data Analytics: Harnessing Insights from Data-Driven Approaches},
  howpublished = {EasyChair Preprint 12482},
  year      = {EasyChair, 2024}}