Concentric AI announced
that its Semantic Intelligence DSPM solution now offers data lineage
functionality for organizations to better protect their data, making it
the first DSPM solution to deliver this differentiated capability.
As a result of today's update to Concentric AI's Semantic Intelligence,
organizations can now make better business decisions around securing
their data by understanding data's entire journey with a clear and
comprehensive view of how it is sourced, processed, modified, entitled,
and consumed.
"Concentric AI's new data lineage functionality allows organizations to
trace the lineage of a particular file or data record and discover how
it has travelled through the enterprise with all the appropriate
modifications, ensuring that organizations have a clear understanding of
their data's possible risk," said Karthik Krishnan, Founder and CEO,
Concentric AI. "Organizations came to us to develop this functionality -
the first of its kind in a DSPM solution - and we are pleased to
rapidly respond and deliver on these industry requirements. Our partners
are also now better equipped to meet their customers' demands for this
robust functionality."
While data lineage exists in the industry from other classes of
products, Concentric AI's new functionality is differentiated by
leveraging large language models (LLMs) and semantic analysis to
identify near duplicates of data records (such as 30 different versions
of a redlined contract), where they are located, how they have
proliferated across the organization from first record to the latest,
and who has and had access to them to better protect sensitive data.
This is unique and a capability that is unrivaled in the industry today.
Advantages of data lineage delivered in a DSPM solution include being
able to identify all versions of similar sensitive data across the
organization's data repositories, as well as remediating risk to that
information from inappropriate entitlements, wrong permissioning, and
unauthorized access. In addition, data lineage can help enterprises move
redundant and obsolete data to secondary storage for effective data
management.
Data lineage allows organizations to understand how data flows across
their environment and who has access and has accessed it, in order to
address risks associated with inappropriate access, inaccurate
entitlements and risky sharing, as well as ensure effective data
management. Organizations can make better business decisions from data
protection to data management by understanding data's entire journey and
identifying redundant processes or changes that might affect risk to
sensitive data. In the event of a data breach, understanding data
lineage can help organizations quickly identify the source of the breach
and the affected data, accelerate response time, and improve damage
control.
"Many industries and organizations are subject to strict data
regulations such as GDPR (the General Data Protection Regulation) and
CCPA (the California Consumer Privacy Act)," added Krishnan. "Data
lineage helps organizations demonstrate compliance by showing regulators
how data is handled, processed and stored. It also creates an audit
trail, making it easier for reporting around regulatory inquiries and
audits."
Concentric AI's Semantic Intelligence DSPM solution scans organizations'
data, detects sensitive or business critical content, identifies the
most appropriate classification category, and automatically tags the
data. Concentric AI uses artificial intelligence (AI) to improve
discovery and classification accuracy and efficiency to avoid endless
regex rules and inaccurate end user labeling. In addition, Concentric AI
can monitor and autonomously identify risk to financial and other data
from inappropriate permissioning, wrong entitlements, risky sharing, and
unauthorized access. It can automatically remediate permissions and
sharing issues or leverage other security solutions and cloud APIs to
quickly and continuously protect exposed data.
Concentric AI's Semantic Intelligence automates unstructured and
structured data security using deep learning to categorize data, uncover
business criticality and reduce risk. Its Risk DistanceTM analysis
technology uses the baseline security practices observed for each data
category to spot security anomalies in individual files. It compares
documents of the same type to identify risk from oversharing,
third-party access, wrong location, or misclassification. Organizations
benefit from the expertise of content owners without intrusive
classification mandates, with no rules, regex, or policy maintenance
needed.