Big Data Analytics (Paperback)

Mansaf Alam

ISBN 10: 1032310448 / ISBN 13: 9781032310442

Published by Taylor & Francis Ltd, London, 2024

About this Item

Paperback. Big Data Analytics: Digital Marketing and Decision-Making covers the advances related to marketing and business analytics. Investment marketing analytics can create value through proper allocation of resources and resource orchestration processes. The use of data analytics tools can be used to improve and speed decision-making processes.Chapters examining analytics for decision-making cover such topics as: Big data analytics for gathering business intelligenceData analytics and consumer behaviorThe role of big data analytics in organizational decision-makingThis book also looks at digital marketing and focuses on such areas as: The prediction of marketing by consumer analyticsWeb analytics for digital marketingSmart retailingLeveraging web analytics for optimizing digital marketing strategiesBig Data Analytics: Digital Marketing and Decision-Making aims to help organizations increase their profits by making better decisions on time through the use of data analytics. It is written for students, practitioners, industry professionals, researchers, and faculty working in the field of commerce and marketing, big data analytics, and organizational decision-making. This book includes various topics related to marketing and business analytics. It is written to help organizations increase their profits by making better decisions. This book is meant for students, practitioners, industry professionals, researchers, and faculty working in the field of commerce, marketing, and big data analytics. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Seller Inventory # 9781032310442

Bibliographic Details

• Title: Big Data Analytics (Paperback)
• Publisher: Taylor & Francis Ltd, London
• Publication Date: 2024
• Language: English
• ISBN 10: 1032310448
• ISBN 13: 9781032310442
• Binding: Paperback
• Condition: new

About this title

Synopsis

Big Data Analytics: Digital Marketing and Decision-Making covers the advances related to marketing and business analytics. Investment marketing analytics can create value through proper allocation of resources and resource orchestration processes. The use of data analytics tools can be used to improve and speed decision-making processes.

Chapters examining analytics for decision-making cover such topics as:

• Big data analytics for gathering business intelligence
• Data analytics and consumer behavior
• The role of big data analytics in organizational decision-making

This book also looks at digital marketing and focuses on such areas as:

• The prediction of marketing by consumer analytics
• Web analytics for digital marketing
• Smart retailing
• Leveraging web analytics for optimizing digital marketing strategies

Big Data Analytics: Digital Marketing and Decision-Making aims to help organizations increase their profits by making better decisions on time through the use of data analytics. It is written for students, practitioners, industry professionals, researchers, and faculty working in the field of commerce and marketing, big data analytics, and organizational decision-making.

About the Author

Dr. Kiran Chaudhary is an assistant professor in the Department of Commerce at Shivaji College, University of Delhi. She has 12 years of teaching and research experience. She earned her Ph.D. in Marketing from Kurukshetra University, India. Her areas of research include marketing, human resource management, organizational behavior, and business and corporate law. She is a distinguished student winning various awards of recognition. She is a book author as well as conference and journal paper author.

Dr. Mansaf Alam is a professor in the Department of Computer Science, Faculty of Natural Sciences, at Jamia Millia Islamia University, New Delhi, India. He has also been a Young Faculty Research Fellow for the Ministry of Electronics and Information Technology in India and editor-in-chief of the Journal of Applied Information Science. As a journal and conference paper author, he conducts research in such areas as big data analytics, machine learning and deep learning, cloud computing, cloud database management systems, object-oriented database systems, information retrieval, and data mining. His other academic activities include: journal reviewer, member of conference program committees, journal editorial board member, and book author.