Protected business intelligence
Trūata Pioneer Explore allows analysts and data scientists to run queries over sensitive data without ever seeing the underlying data or being able to re-identify or infer attributes about individuals from returned results.
Organizations gain greater control over their sensitive data and increased confidence that it will be used compliantly and responsibly.
Protect data privacy, integrity
and security
Separate the analyst from the
source data
Make responsible data-driven decisions based on more accurate insights
Activate data across your organization with confidence
An advanced business intelligence tool for privacy-first enterprises
How does Pioneer Explore work?
01
It ensures that the analyst does not have access to granular underlying data or any values that could lead to re-identification or attribute inference of individuals or sensitive entities
02
Users can query the secure raw data in order to define and develop business intelligence outputs
03
Each submitted query and the related results are analyzed and filtered to ensure the outputs delivered meet the organization’s data protection, confidentiality and compliance requirement
Business rules to accelerate analysis
By applying a user-common set of rules across their entire data universe, an organization can be more confident about the compliant and responsible use of sensitive data.
Features
A protective layer to manage multiple risks
Configurable rules
Organizations benefit from greater control over the sensitive data they hold; the level of access granted to the user and critically, the queries that can be run and the outputs that are returned. This minimizes the risk of unauthorized use, re-identification of specific individuals and the manipulation of sensitive data.
Enhanced transparency and accountability
All queries are recorded so anomalous behavior can be proactively identified, managed and audited. These audit trails ensure compliance with regulatory requirements and facilitate breach incident investigation, if necessary.
Greater data protection
Disclosure control techniques such as differential privacy, regular noise addition and rounding add a controlled amount of noise to the output data. This prevents anyone with access to the output data from re-identifying or inferring attributes of specific individuals.
Learn more about Trūata Pioneer Explore
Get in touch with Trūata, and one of our friendly experts will explain how Pioneer Explore can provide you with a competitive advantage.