DDR solutions are important because they help address the vulnerabilities of cloud data distributed across multiple platforms, applications, data stores and software as a service (SaaS) environments.
The open and interconnected nature of cloud computing can place sensitive information such as customer data, personally identifiable information (PII) and financial data at risk.
The IBM Cost of a Data Breach Report found that 40% of data breaches involve data stored across multiple environments. Data stolen from public clouds incurred the highest average breach cost at USD 5.17 million.
With data privacy regulations expanding and global data breach costs at an all-time high, effective cloud data security strategies are a business imperative.
Security solutions such as endpoint detection and response (EDR), extended detection and response (XDR) and firewalls protect against data threats at the network and device levels. However, because network perimeters are often porous in cloud-connected networks, these security measures provide limited protection when data travels or exists simultaneously across multiple systems.
In contrast, DDR operates beyond network perimeters. It monitors and protects the data itself regardless of location.
Using data discovery and data classification, DDR pinpoints the location of sensitive data. DDR then tracks the data's movement and usage across multicloud environments.
Advanced analytics and anomaly detection capabilities enable DDR tools to identify malicious data activity or user behavior. For example, unauthorized access, massive downloads of information, late-night data transfers or an IP address from an unusual location might signal a cyberattack.