The use of behavioural analytics for the identification and mitigation of risks in the field of data security represents a paradigm shift: the process of threat detection is optimized from a metadata collection towards an analytical modeling. Behavioral Analytics collects a wide range of information and analyzes in real-time patterns and relationships that are created by the habits and activities of users and their devices. Events that do not meet the normal user behavior are filtered out immediately as soon as they emerge. These anomalies may represent attacks both from within and from outside. In such cases, the analysis tool detects the attack and automatically triggers an alert. As a result, necessary investigations or further steps can be initiated immediately to counter the possible threat before the data is effectively at risk.