Data insight to act effectively
While privacy begins with data discovery, the second part is visualization with dashboards for data insight around risk impact. Data insight delivers the understanding to act effectively on data to protect what matters most, to minimize the data that is redundant, obsolete, and trivial (ROT), and to apply life cycle data policies based on context, data age, permissions, relevancy, and risk. Data insight enables organizations to effectively act upon and manage data for risk mitigation and privacy compliance.
“Data Discovery allowed us to effectively find and understand our data risk. The insights we found from the analysis were invaluable in taking effective actions to protect our data and monitor it going forward.”
Kadir Yildiz, CISO, Turkish Airlines
Understand your data
Content analysis and data discovery can drive key business decisions, while improved insight helps protect critical business data, reducing risk while enabling secure information sharing—building a foundation for better risk management and privacy practices that build trust with customers. If organizations can demonstrate that they have developed a risk management and privacy practice built on protecting customer data and establishing trust, it can become a very compelling differentiator to harness for the business.
Voltage Data Discovery solutions support a broad range of repositories, and over 1,000 different data formats, to analyze and protect sensitive data across the enterprise—in structured data across databases and data applications and unstructured data in on-premises and cloud repositories.
Without the appropriate level of controls and protection, structured applications and databases can grow and add further risk, if left unsupervised. Connecting to disparate data repositories to evaluate the underlying risk across your ecosystem on-premises and in the cloud is a crucial step towards protecting data. Voltage Structured Data Manager can discover, analyze, and classify data in on-premises, cloud, and hybrid systems to enable policy-based data disposition—for archival, protection, deletion, or other disposition based on company policy.
Discover, analyze, and classify sensitive data in database repositories, automate risk remediation
of data is unstructured
PII Detection—Understanding Context
Detecting personally identifiable information (PII) and personal information (PI) is at the core of protecting sensitive data. With over 80% of data being unstructured, the challenge shifts from simply detecting sensitive data to accuracy, confidence, and reducing false positives. Simple pattern matching will not be adequate in tackling today’s data discovery workloads. You will need to understand, not only that a pattern match exists, but that the context of that pattern along with the contents of the document or file indicates that it is a “true” positive and should be protected.
Context is critical to identifying sensitive data.
Voltage File Analysis Suite (FAS) leverages AI-driven rule sets and grammars out of the box to describe sensitive data entities that need to be identified and protected. Our core grammar sets focus on:
- PII—Personally Identifiable Information, including 13 categories of entities across 39+ different countries
- PHI—Protected Health Information, normally associated with the North American health industry
- PCI—Payment Card Industry data such as credit card and primary account numbers
- PSI—Personal security information, for account details access keys
Data insight enables risk reduction through data minimization
CIOs are looking for ways to reduce data risk through data minimization, frequently as part of IT modernization projects, such as accelerating to cloud and application retirement. FAS customers can perform regular Redundant Obsolete Trivial (ROT) analysis and do clean-up to remove duplicate and obsolete data that has no more business relevance, such as 20-year-old customer purchasing histories.
Learn more: Discover, classify, and protect sensitive data in media files with File Analysis Suite.
Voltage Data Discovery solutions use AI to be context-aware, to intuitively identify risk and minimize false positives, not only through context but also the depth and breadth of personal data detection. Data is analyzed in place, without making extra copies.
Sampling, Tagging and Enrichment Prioritizing your data discovery projects is critical. Voltage Data Discovery provides risk-based random sampling across both structured applications and unstructured repositories highlighting risk and helping guide future efforts to assess and mitigate risk. Categorization of sensitive data can be automated, tagged, and metadata enriched based on pre-built sensitive data grammars and classifications. These grammars are highly precise, contextually aware analyses that help support a broad range of privacy regulations, including GDPR, CCPA, PIPEDA, POPI, KVKK, as well as Payment Card Industry (PCI), Protected Health Information (PHI) and custom use cases.