As growing volumes of diverse data are channeled into the data lake, it becomes a centralized source of vital and often highly sensitive business data. In recognition of the need to protect business and customer data, enterprise-grade data lake security has been an integral part of Graal Data Platform.
Use Cases
The integration of Graal Platform represents a paradigm shift for enterprise big data governance and security. By integrating Graal, enterprises can now implement dynamic classification-based security policies, in addition to role-based security. Graal platform empowers data administrators to define security policy based metadata tags or attributes and apply this policy in real-time to the entire hierarchy of data assets including databases, tables and columns.
Dynamic data masking enables Graal security administrators to ensure that only authorized users can see the data they are permitted to see, while for other users or groups the same data is masked or anonymized to protect sensitive content. The process of dynamic data masking does not physically alter the data, or make a copy of it. The original sensitive data also does not leave the data store, but rather the data is obfuscated when presenting to the user.
Graal Platform provides the most comprehensive centralized platform to define, administer and manage security policies consistently.
Graal Platform provides administrators with deep visibility into the security administration process that is a prerequisite to complying with enterprise data governance audits. The combination of a rich user interface and deep audit visibility provides answers to auditor’s questions and enhances the productivity of data lake security administrators. Graal also provides a centralized framework to collect and report on access audit history, including the ability to filter on various parameters.