Data discovery is a foundational element of any type of data management: from cybersecurity to data privacy to data governance. Discovery is at the core of data intelligence, insight, and analysis – and needs to be both scalable and automated in order to successfully address the volume (and type) of data that organizations collect.
Effective (and sustainable) privacy, security, and governance programs require discovery in-depth: empowering organizations to scratch more than just the surface of their data. That means not only finding and identifying more types of sensitive and personal data with greater accuracy, but being able to apply context, insight, and perspective to that data – which then helps inform policy and controls.
It’s no longer enough to only be able to identify regular expressions and common types of sensitive data (like credit card numbers or social security identifiers). Unlike earlier regulations, today’s data privacy initiatives focus on data that can be related to an individual, which means that data discovery solutions need to be able to identify personal data not just by type, but from contextual clues and relationships to other data points.
Privacy-centric data discovery (a must for data privacy and cybersecurity in today’s environment) requires a multi-pronged strategy to identify all types of sensitive & personal data in an organization – and that strategy starts with discovery in depth.
The solution empowers organizations to know their data – and gain the insights they need for privacy, protection, and perspective. A discovery in-depth approach gives 360° visibility to sensitive data and deep data intelligence across all types of data, across all data stores.
Privacy-centric data discovery requires a multi-pronged strategy to identify and identify relationships between all types of sensitive & personal data in an organization – and that strategy starts with discovery in depth.
- Discover, inventory, and map all types of data across the enterprise IT infrastructure
- Automatically discover dark and inferred data
- Identify sensitive & personal data and at-risk data
- Visualize entity correlation for privacy alignment
- Go beyond compliance checklists with a framework for privacy & risk management