Data Engineering for Data-Driven Marketing

Balamurugan Balusamy, Veena Grover, M. K. Nallakaruppan, Vijay Anand Rajasekaran, Mariofanna Milanova, Balamurugan Baluswamy

• Publisher: Emerald Publishing Limited
• Year: 2025
• Print ISBN: 9781836623274
• eBook ISBN: 9781836623267
• Topic: Business
• Subtopic: Decision Making
• Index: Business

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.

Table of contents

• Half Title Page
• Title page
• Copyright Page
• Contents
• About the Editors
• About the Contributors
• Chapter 1: Exploring AI in Data-driven Marketing: Understanding the Intersection of Data Engineering and Marketing
• Chapter 2: Architecting for Success: Designing Robust Data Infrastructures to Power Data-driven Marketing Campaigns
• Chapter 3: AI in Data-driven Marketing: Decoding Consumer Choices and Behaviours
• Chapter 4: Ingesting Insights: Data Ingestion Strategies and Techniques for Marketing Data
• Chapter 5: Mastering Data Transformation: Preparing Marketing Data for Actionable Insights
• Chapter 6: Seamless Data Flow: Constructing End-to-End Data Pipelines for Real-time Marketing Analytics
• Chapter 7: Crafting Customer Profiles: Data Engineering for Comprehensive Customer Understanding
• Chapter 8: Empowering Personalized Marketing: Leveraging Data Engineering for Customer Segmentation
• Chapter 9: Quality Assurance in Marketing Data: Ensuring Accuracy and Reliability
• Chapter 10: Integrating Marketing Data Ecosystems: Merging Diverse Data Sources for Holistic Insights
• Chapter 11: Data Security in the Age of Marketing: Safeguarding Customer Information and Compliance
• Chapter 12: Harnessing AI and ML for Marketing: Integrating Advanced Analytics Into Data-Driven Strategies
• Chapter 13: Ethics and Privacy in Data-driven Marketing: Navigating Legal and Ethical Considerations in the Age of Big Data
• Chapter 14: Unlocking the Potential of Data Lakes: Organizing and Storing Marketing Data for Analysis
• Chapter 15: Optimizing Outcomes: Professional Perspectives on Data-driven Marketing Mastery