Data protection for privacy by default
Voltage Data Discovery enables organizations to gain a deep understanding of the data contained within structured and unstructured data repositories. This understanding helps detect value and risk, and protect sensitive and high-value data, while providing flexible approaches that evolve to serve your needs over the different use cases throughout the lifecycle of your data.
Download this report to learn why Voltage Structured Data Manager and Voltage SecureData, are named the ‘Leader’ in Dynamic Data Masking solutions!
The number of cyber-attacks against enterprises and governments globally, continues to grow in frequency, severity, and cost according to the Ponemon Institute 2021 Cyber Crime Study*. “Mega” breaches now reach over $400M to resolve.
Actionable Outcomes: Data Protection
If data is the new currency, data protection is the central bank for an organization looking to protect its assets and preserve their worth. Voltage data protection is powered by our patented data security and encryption capabilities. Voltage integration of data discovery with data protection ensures that when sensitive data is detected, Voltage data security can protect and secure the data in place, in motion, and while in use. The flow of business continues securely as data is accessible for business users— and blocked or rendered harmless for unauthorized users.
GDPR Article 32 – Security of Processing
“…the controller and the processor shall implement appropriate technical and organizational measures to ensure a level of security appropriate to the risk, including…the pseudonymization and encryption of personal data…”
Voltage data security integrated into the data discovery process flows protects data:
- Inside structured business applications where sensitive data is encrypted at field level using Voltage SecureData with format-preserving encryption (FPE), secure stateless tokenization (SST), or format-preserving hash (FPH). Voltage tokenization methods pseudonymize any structured data type.
- Inside analytics platforms and data lakes where it enables secure data analytics for faster insights and reduced risk of a breach or proliferation of sensitive data.
- Inside archived data repositories where data is kept for data preservation and records compliance obligations. Sensitive data is protected inside the official record contained within a data archive ensuring data usage, permissions, and retention schedules are met.
- At the endpoints based on transparent and persistent policies beyond the edge of the network with Voltage SmartCipher file level encryption for unstructured data.
Voltage can mask or intelligently encrypt the database data in place by acting on production instances while ensuring data integrity. This allows you to manage not only archive databases, but the full relational database management system (RDBMS) lifecycle—protecting all data and adhering to the latest regulatory guidelines.
Secure and Compliant Test Data Management
The power of the Voltage portfolio is demonstrated by Data Privacy Manager in generating test data and automatically anonymizing personal data for application testing. This Voltage solution protects customer data during testing, Quality Assurance (QA), and related functions, and streamlines the pipeline between development, test, and production.
Secure Cloud Analytics
With enterprises capturing personal information, intellectual property, health information, and more new classes of sensitive data than ever before, information in analytics platforms or a data lake can form toxic combinations that present significant risk to the organization. Organizations need to minimize the risk associated with secure data analytics while ensuring analysts can still safely and securely run queries and reports on trends and business patterns. At the same time, they need to ensure the approach will also help comply with data privacy regulations and risk mitigation around a data breach.
Critical customer use cases
Voltage data protection capabilities enable organizations to pseudonymize or anonymize sensitive data by design across use cases including test data management, cloud analytics, data subject requests, consent management, IT modernization, and more. What are your top priority data privacy and protection projects?