Data Lifecycle Security for Cloud Data Stores

Automated Visibility, Governance, and Protection for Cloud Data Warehouses & Data Lakes (based on privacy-preserving algorithms and data-protection research at UC Berkeley)

Automated Cloud Data Security

Dasera automatically finds where sensitive data is stored, understand how it is used, detects risky behaviors, and prevents incidents

Data Classifications and Usage Insights

Discover where sensitive data is located, track where it moves to, and identify risky behavior

Fine-Grained Governance and Control

Enforce role and team-based policies that govern how sensitive data should be used

Automated Remediation Options

Get real-time alerts for incidents and respond with customizable remediation options

Building the Future of Safe Data in the Cloud

Dasera Radar

Non-Invasive Visibility into Cloud Data and Risky Use

  • Identifies where sensitive data is stored and how it is used in cloud data warehouses and data lakes
  • Prevents privacy and exfiltration exposures through proprietary query analysis alerts
  • Enables easy customization of risk posture to reflect business and compliance needs
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Dasera Interceptor

Automatic Data Protection from Risky Interactions

  • Reduces risk of credential theft through real-time incident response using templated workflows
  • Protects data through optional inline query rewriting and context-based access control
  • Delivers personalized feedback and recommendations to all employees who use sensitive data

Works With

Join Other Forward-looking Cybersecurity Leaders

Learn from best practices shared in Red Book of Insider Threats

Julie Tsai
Head of InfoSec, Roblox
We can't protect what we don't know. Flag and correlate for simple indicators or what shouldn't be happening.
Jitendra Joshi
Head of Information Security, BetterUp
In the post-COVID world, perimeters have disappeared and the line between insiders and outsiders has blurred.
Sujeet Bambawale
Bad actors may choose to attempt a different tact… making it easier for insiders to accidentally misroute confidential information
Andy Kim
People are highly complex in terms of what motivates them, e.g. someone with financial problems may think they are entitled to a share of company profits.
Chris Donewald
Privacy Counsel, Affirm
Companies should implement, enforce, and, perhaps most importantly, regularly updates policies and controls to account for routine uses of data and any new uses of data.
John Hluboky
Principal Security Architect, Allscripts
Leveraging machine learning to rapidly cull through the growing mountain of data and provide actionable alerts with minimal false positives is where the industry is moving.

Read the Data Lifecycle Trust & Privacy Report

Findings from the Q1 2021 survey reveal what makes consumers trust and distrust brands with their data