Data science is the set of methods used to collect, clean, analyze, and model data so people or systems can make better decisions. It combines statistics, programming, domain knowledge, and sometimes machine learning to turn raw logs, records, and sensor feeds into usable signals. In practice, the quality of the input matters as much as the model itself: biased, incomplete, or mislabeled data can produce misleading results.
In cybersecurity, data science helps defenders spot anomalies in network traffic, detect phishing patterns, prioritize alerts, and improve threat intelligence. It is also relevant to attackers, who may use large datasets to profile targets, automate reconnaissance, or tune social engineering at scale. Because so much security tooling depends on data, strong data science skills support better governance, safer automation, and more reliable AI systems. Poor data handling, by contrast, can create blind spots, false positives, and dangerous trust in outputs that have not been properly checked.