Every second, billions of data points are generated as people browse, shop, and interact online. But who's collecting this data and how are they using it to target you with ads? This study is about the application of data science and database systems in digital marketing to offer personalized internet advertisements. The study reviews literature and analyzes current industry practices to explore how machine learning algorithms collect, store, and process consumer data to serve targeted ads in real time. The results show that modern marketing makes heavy use of behavioral data, predictive modeling, and automated decision-making for the optimization of advertising effectiveness. This creates huge value for businesses but also raises urgent issues of transparency and user privacy. The paper concludes by arguing that ethical guidelines and privacy-oriented technologies are urgently needed to make data-driven marketing work for people, not just profits.