Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry
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Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry

Valentina Chkoniya (University of Aveiro, Portugal)
Projected Release Date: August, 2021|Copyright: © 2022 |Pages: 626|DOI: 10.4018/978-1-7998-6985-6
ISBN13: 9781799869856|ISBN10: 1799869857|EISBN13: 9781799869863
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Description

The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries.

The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Applied Artificial Intelligence
  • Applied Data Science
  • Big Data
  • Business Intelligence
  • Consumer Behavior Analytics
  • Customer Experience
  • Customer Response Modeling
  • Data Science
  • Deep Learning
  • Digital Marketing Analytics
  • Ethics
  • Fraud Detection
  • Logistic and Supply Chain
  • Machine Learning
  • Market Monitoring
  • Marketing Intelligence
  • Marketing Strategy Analytics

Table of Contents and List of Contributors

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