Data Privacy Laws Are Changing the Landscape of Test Data Management

Many companies have been using real production data to make sure that application testing is relevant and captures the variety of use cases they may have. Production data inevitably includes sensitive personal data.

Data privacy laws (such as GDPR, CCPA, and KVKK) now prohibit and obligate companies to protect citizen data even when consumed internally. Some organizations sub-contract their testing, Quality Assurance (QA), and training processes to third parties located in different countries, exposing citizen data to non-authorized users. Such practices are automatically non-compliant with data privacy law.

To enable data privacy, businesses need to ensure that every data element is identified, classified, and protected according to the population of users and policies.

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Discover a secure and compliant approach to Test Data Management

Voltage Data Privacy Manager provides a comprehensive solution to address the privacy governance needs of enterprises with sensitive structured data. It provides a single solution for sensitive data discovery, extraction, and anonymization, to deliver test data that closely matches production data and is compliant with data privacy regulations. As it offers a range of data protection techniques, Data Privacy Manager also enables customers to manage and protect sensitive structured data throughout its lifecycle, from discovery and classification to protection and disposition.

Discover Private Data in Databases

Find sensitive structured data in active and inactive systems across the enterprise.

Enable Data Privacy in Non-Production Environments

Analyze and classify data such as names, social security numbers, IDs and more based on-pre-set libraries.

Anonymize the Data for Secure Use Whether for Analytics, Test, or Other Use Cases

Enforce centrally-set privacy and security policy and manage data across the enterprise from a single pane of glass (e.g., move, delete, quarantine, notify or protect

Shield Real Data Sources with a Protected Test Data Repository Containing Realistic Fake Data

Mask or Pseudonymize sensitive data using encryption and tokenization, protecting privacy while keeping it usable for business processes and analytics.

Ensuring That the Real Sensitive Data Is Secure

Document every action taken throughout the process and generate reports for compliance audits.

Produce Private Data

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