Privacy is about peoples' data. Find it across a diverse data ecosystem with deep search, correlation, and context for inferred PI datasets not directly tied to and identity.
Replace manual surveys with a centralized, consistent, and defensible inventory. Reduce friction with data owners and empower risk decisions on actual data.
Prioritize protection with an accurate data risk map. Quantify data breach exposure by data subject count, classification and regulatory impact. Respond with on-demand deep search.
Metadata cataloging is helpful but not defensible for GDPR and CCPA which require knowing precisely which data elements a company has on a consumer, where, and for what purpose. In addition, data protection requires knowing precisely where sensitive data resides within a dataset.
Integris operates at the data element level to inform you exactly what’s in the dataset, not just what the metadata implies.
The most challenging aspect of fulfilling data subject requests (DSRs) is finding data subjects across your data ecosystem.
Integris identifies the data subject’s relevant PI, as well as the specific systems, tables, and files that contain the subject’s personal information along with purpose, PI categories, system owner, and related information.
Data lakes are becoming data dumpsters. Before providing access to additional business users or data scientists, ensuring that PI cannot be reasonably re-identified will reduce the risk of an inadvertent privacy issue.
Integris identifies combinations of data that alone are benign, but when combined are high risk. For example, 87% of the US population can be re-identified using only three attributes: gender, zip code, and date of birth.
Understanding inferred personal data is important, yet challenging. For example, food preferences in a user profile can infer religion, donation records can infer political preference, and behavioral patterns can be drawn from geospatial data.
Integris understands data context in order to identify inferred attributes.
Multi-zone support means there’s no need to copy consumer data across geographic regions or security zones. By default, Integris obfuscates PI from the UI.
Integris deploys in your secure data environment - on-prem, in your AWS, Azure, or GCP virtual private cloud, or both. It is not a SaaS solution and your data is not sent to Integris.
Privacy is a big data problem. Integris’ modern, microservices architecture and administrative controls adeptly handle the volume, variety, and velocity of big data.
Integris data processing services containers can be deployed close to your data repositories minimizing network traffic and leveraging your existing compute power.
Integris is able to connect to any data source type, at rest or in-motion, structured, unstructured, on-prem, or in the cloud.
This extends to data formats such as pdf, csv, docs, and even includes XML, JSON, or any other textual data format.