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Beziehungsmarketing 2 Relationship marketing 2 Artificial intelligence 1 Big Data 1 Big data 1 Business ethics 1 Canada 1 Consumer behaviour 1 Data protection 1 Datenschutz 1 Ethics 1 Ethik 1 Großbritannien 1 Kanada 1 Konsumentenverhalten 1 Künstliche Intelligenz 1 Market integration 1 Market segmentation 1 Marketing management 1 Marketingmanagement 1 Marktintegration 1 Marktsegmentierung 1 Product quality 1 Produktqualität 1 Quality management 1 Qualitätsmanagement 1 Target group 1 United Kingdom 1 Unternehmensethik 1 Zielgruppe 1
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Undetermined 16
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Article 16
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English 16
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Grover, Veena 4 Benedetto, Francesco 2 Nallakaruppan, M. K. 2 Anitha, A. 1 Anitha, K. 1 Balusamy, Balamurugan 1 Chakraborty, Anuradha 1 Charanya, R. 1 Chenxi, Wang 1 Dogra, Mahima 1 Gangwar, Veer P. 1 Gill, Rubina 1 Hasan, Fatima Qasim 1 Ilakkiyaa, U. 1 Jain, Mridul 1 Kaur, Amandeep 1 Konecna, Zdenka 1 Krishnan, Siva Karthikeyan 1 Kumar, Harmesh 1 Kumar, Pankaj Raj 1 Magesh, R. 1 Mangairkarasi, V. 1 Nandal, Manju 1 Pal, Purnima 1 Patel, Mastu 1 Paul, Trisha 1 Pelusi, Danilo 1 Pethani, Ansh 1 Ponnusamy, Kumaravel 1 Prasad, Aditya 1 Preetha, S. 1 Raju, Valliappan 1 Ramachandran, K. K. 1 Rastogi, Tejasv 1 Roy, Soumendra 1 Sachdeva, Channi 1 Sahu, Divya 1 Sam, Annie 1 Sarkar, Amit 1 Shanthini, R. 1
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Data engineering for data-driven marketing 16
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ECONIS (ZBW) 16
Showing 1 - 10 of 16
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Prelims
In: Data engineering for data-driven marketing, (pp. i-xxii). 2025
Persistent link: https://www.econbiz.de/10015646401
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Chapter 13. Ethics and Privacy in Data-driven Marketing: Navigating Legal and Ethical Considerations in the Age of Big Data
Singh, Manisha; Hasan, Fatima Qasim - In: Data engineering for data-driven marketing, (pp. 187-198). 2025
This chapter addresses the complex interplay of ethics, privacy, and legal issues in the realm of data-driven marketing. Ethical and privacy concerns dominate marketers in today’s time of ever-expanding data and increasing data analysis sophistication. This chapter outlines the significance of...
Persistent link: https://www.econbiz.de/10015646404
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Chapter 12. Harnessing AI and ML for Marketing: Integrating Advanced Analytics Into Data-Driven Strategies
Nallakaruppan, M. K.; Benedetto, Francesco; Jain, Mridul - In: Data engineering for data-driven marketing, (pp. 179-186). 2025
This chapter introduces the specifics and intricacies of data security in marketing applications, more specifically aiming towards an organization’s responsibility and need to protect their own and their customer’s data. From identifying and understanding vulnerabilities to finding effective...
Persistent link: https://www.econbiz.de/10015646405
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Chapter 9. Quality Assurance in Marketing Data: Ensuring Accuracy and Reliability
Sinha, Arvind Nath; Srivastava, Vibha; Sinha, Kashvi - In: Data engineering for data-driven marketing, (pp. 121-142). 2025
We live in a data-driven world where success relies on the accuracy of information and data quality assurance (QA). This chapter delves into the intricacies of establishing a robust data QA framework, empowering you to navigate the ever-evolving data landscape with confidence. This chapter...
Persistent link: https://www.econbiz.de/10015646408
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Chapter 8. Empowering Personalized Marketing: Leveraging Data Engineering for Customer Segmentation
Grover, Veena; Dogra, Mahima; Sahu, Divya; Nandal, Manju - In: Data engineering for data-driven marketing, (pp. 105-119). 2025
In an era of customer-oriented approaches, personalized marketing is crucial for business success in order to formulate important strategies. In the ever-changing landscape of the current economic situation, personalized marketing has come to offer a crucial technique for establishing intimate...
Persistent link: https://www.econbiz.de/10015646409
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Chapter 7. Crafting Customer Profiles: Data Engineering for Comprehensive Customer Understanding
Chakraborty, Anuradha; Roy, Soumendra; Sarkar, Amit - In: Data engineering for data-driven marketing, (pp. 91-104). 2025
The main focus of this chapter is to understand the role of data engineering in crafting customer profiles. The idea of data engineering is familiar; it helps companies better understand their clientele. Any firm in today’s digital environment has to apprehend and comprehend data engineering...
Persistent link: https://www.econbiz.de/10015646410
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Chapter 15. Optimizing Outcomes: Professional Perspectives on Data-driven Marketing Mastery
Prasad, Aditya; Rastogi, Tejasv; Paul, Trisha; Tyagi, … - In: Data engineering for data-driven marketing, (pp. 217-235). 2025
This technological phase completely discovers the vibrant domain name of data-driven advertising diving right into its meaning, significance, as well as present landscape with a certain concentrate on expert system (artificial intelligence (AI)), customization, plus consumer understandings. The...
Persistent link: https://www.econbiz.de/10015646402
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Chapter 14. Unlocking the Potential of Data Lakes: Organizing and Storing Marketing Data for Analysis
Magesh, R.; Ilakkiyaa, U.; Shanthini, R.; Charanya, R. - In: Data engineering for data-driven marketing, (pp. 199-216). 2025
Marketing data can help marketers understand their consumers, habits, and preferences better. Companies are ready to add social media, browsing logs, text analytics, and sensor data to traditional data centres so that they will be able to get a full picture about customers. Nevertheless, having...
Persistent link: https://www.econbiz.de/10015646403
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Chapter 11. Data Security in the Age of Marketing: Safeguarding Customer Information and Compliance
Nallakaruppan, M. K.; Pethani, Ansh; Pelusi, Danilo - In: Data engineering for data-driven marketing, (pp. 165-178). 2025
This chapter introduces the specifics and intricacies of data security in marketing applications, more specifically aiming towards an organization’s responsibility and need to project their own and their customer’s data. From identifying and understanding vulnerabilities to finding effective...
Persistent link: https://www.econbiz.de/10015646406
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Chapter 10. Integrating Marketing Data Ecosystems: Merging Diverse Data Sources for Holistic Insights
Gill, Rubina; Kumar, Pankaj Raj; Patel, Mastu; Kumar, … - In: Data engineering for data-driven marketing, (pp. 143-163). 2025
This chapter highlights the importance of combining multiple data sources to gain a complete understanding of the marketing environment. Marketing campaigns can be successful only by data-driven decision-making. We need to include multiple data sources so that it may furnish a complete and...
Persistent link: https://www.econbiz.de/10015646407
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