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Unlock the value of data without increasing risk, while also minimizing storage cost. Oracle Data Masking and Subsetting helps organizations achieve secure and cost-effective data provisioning for a variety of scenarios, including test, development, and partner environments.
Join the Oracle database security monthly community call.
Discover and classify sensitive data to understand risk and aid in designing data protection policies.
Determine referential relationships and create models to protect data integrity during data masking and subsetting operations.
Remove sensitive data from test, development, analytics, and other non-production environments.
Flexible masking techniques preserve data characteristics to support continued application functionality after data masking.
Further reduce the effort required and maximize time to value with pre-built masking templates for Oracle E-Business Suite and Oracle Fusion Applications.
Create smaller data sets to save time and storage costs. Improve efficiency while reducing risk.
Multi-factor subsetting techniques create representative, relevant, and functionally intact data sets.
Eliminate overhead on production by masking in-database, or use in-export masking to eliminate the need for staging environments.
Leverage the power of Oracle Database to minimize the time and resources required to create non-production databases.
Mask and subset data in non-Oracle databases using Oracle Database Gateways, which is always included.
Oracle Advanced Security, Oracle Data Masking and Subsetting Pack, and Oracle Active Data Guard enable us to go beyond what is required by privacy laws, ensuring access to citizens’ personal data is secure and trackable. Oracle’s solutions are a proven investment in peace of mind and security.Jose Luis Fernández Carrión
Minimize data exposure in non-production environments by discovering and masking sensitive data and sharing only relevant data.
Leverage data masking and subsetting policies to demonstrate data protection by design and default to auditors.
Safely share realistic, representative, and functionally intact data with relevant stakeholders to fuel test, development, and other initiatives.
Reduce time, storage, and infrastructure costs by extracting and sharing only relevant data.