Data science provides a effective analysis tool for identifying threat patterns and predicting potential attacks based on historical data of cybersecurity incidents. This section will focus on how data science approaches are integrated into critical security structures such as intrusion detection systems (IDS) and intrusion prevention systems (IPS) used to detect and prevent cyber threats. In this context, important techniques such as machine learning, big data analytics, and anomaly detection methods will be detailed. The aim of the section is to understand the critical role of data science techniques in cybersecurity and to demonstrate how these techniques are applied in practice. At the same time, it is aimed to inform readers about the current state of cybersecurity analytics and to provide a glimpse into where this field may evolve in the future.