Harnessing Big Data Processing in Computer Networks for Digital Marketing Entrepreneurship

Abstract

This research investigates the integration of big data processing in computer networks for digital marketing entrepreneurship to optimize marketing strategies and drive business growth. By analyzing current digital marketing practices, we identify key challenges faced by entrepreneurs. Through examining successful case studies, we showcase the effectiveness of big data processing in marketing campaigns. A practical framework is developed to guide startups and small businesses in integrating big data processing into their marketing strategies, considering factors like customer behavior analysis, segmentation, and personalized marketing. Additionally, we explore scalability and cost-effectiveness concerns, particularly relevant for entrepreneurs with limited resources. Ethical implications of data collection, processing, and utilization are thoroughly examined, and strategies to address challenges and limitations are proposed. Through comparative analysis, we assess the performance of big data-driven marketing campaigns in comparison to traditional approaches, revealing improved outcomes and return on investment. This research provides entrepreneurs with valuable insights and recommendations, empowering them to make data-driven decisions and succeed in the dynamic world of digital marketing. Moreover, it contributes to the discourse on big data in entrepreneurship, promoting responsible and innovative practices in the digital marketing landscape.