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Data engineering for data-driven marketing
Hardback
€116.00
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- Book Synopsis
- In the digital age, data has become the cornerstone of effective marketing strategies. Data Engineering for Data-Driven Marketing explores the vital intersection of data engineering and marketing, providing a comprehensive guide to harnessing the power of data for successful and impactful campaigns. Offering a thorough exploration of the symbiotic relationship between data engineering and modern marketing strategies, Data Engineering for Data-Driven Marketing uses a strategic lens to delve into methodologies of collecting, transforming, and storing diverse data sources. With real-world case studies actionable insights, the chapters within navigate the reader through the intricate process of building robust data pipelines, optimizing data quality, and implementing real-time processing techniques, all tailored to elevate marketing campaigns through precision targeting, customer personalization, and predictive modelling.
- About The Author
- Balamurugan Balusamy is Associate Dean at Shiv Nadar University, Delhi-NCR following being Professor, School of Computing Sciences and Engineering as well as Director International Relations at Galgotias University, Greater Noida, India. Veena Grover is a distinguished Economics professional currently Professor of Economics at Noida Institute of Engineering & Technology, Greater Noida, India. M. K Nallakaruppan is Assistant Professor at the School of Information Technology and Engineering, Vellore Institute of Technology, India. He is an Associate Member of the IEEE and Member of Soft Computing Research Society. Vijay Anand Rajasekaran is Associate Professor in VIT University, India following his time as Senior Technical Lead at HCL-CISCO, India. His contributions focus on Engineering Education, Block chain and Data Sciences. Mariofanna Milanova is Professor in the Department of Computer Science for University of Arizona at Little Rock, USA, and has been a faculty member since 2001. She is an IEEE Senior Member, Fulbright U.S. Scholar, and NVIDIA Deep Learning Institute University Ambassador.
- Product Details
-
- ISBN
- 9781836623274
- Format
- Hardback
- Publisher
- Emerald Publishing, (07 May 2025)
- Number of Pages
- 292
- Weight
- 516 grams
- Language
- English
- Dimensions
- 229 x 152 x 18 mm
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