Self-service analytics that separates the user from the underlying data
Self-service analytics that separates the user from the underlying data

Trūata Pioneer Explore

Self-service analytics
that separates the user
from the data.

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?


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


Users can query the secure raw data in order to define and develop business intelligence outputs


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.

Trūata Pioneer - an advanced business intelligence tool for privacy-first enterprises.


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.