Enterprise data is scattered across an organization’s infrastructure, applications, and services. As a result, the data security risks are distributed across data sources and in transit. Data security posture is the collective assessment of data security risks across an organization. Data security posture is a holistic view of risks determined by
Size and complexity of the surface of data
Size of potential financial loss in the event of a breach
Likelihood of a breach and level of controls
Data is the lifeblood of the data. Data breaches result in financial damage and cause irreparable damage to a company’s reputation and loss of customer trust. Moreover, data protection laws require companies to announce breaches publicly and pay hefty penalties. Therefore, organizations must understand where, what, and the size of risks they hold.
| Data Security Posture | Data Discovery / Mapping | |
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| 360 view of the data | ||
 What personal / sensitive data do we have? |
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| Who has access to it? |
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| Who is using it? |
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| 360 view of the risks | ||
| Identify breach and privacy risks |
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| Prioritize critical risks |
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| Understand trade-offs value vs. risks |
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Security teams have the impossible job of protecting the data while making data ubiquitously available across the organization. We help you identify, prioritize and monitor data security issues without adding friction to your data flows.
Our platform gives visibility into your data, who has access and who is using the data.
We apply AI and risk models to quantify the risks in your data. Prirotize risks based on the risk scores.
Automatically scans for the changes in data structures, data content, and usage. Our solution continuously estimates risk and surfaces issues.
Finds data assets with sensitive data that are over exposed to many users, potentially posing high risk
Identifies in unused data assets that could be archived or deleted, resulting in lower cost and risks.
Lists all the users who have wide access privileges and don’t actively use the data.
Under the hood, we bring multiple disciplines – AI, privacy engineering, risk modeling – to understand your enterprise data environment and find ways to improve your data security posture.
