Identify and Protect PII in Databricks

Databricks data security at your fingertips
Book a demo

Protect and freely share your Databricks data,while protecting PII

Protecto's data privacy intelligence identifies privacy risks by factoring usage, access, sensitivity, and risk associated with your Databricks instance - in just a few clicks.

Step 1: Gain visibility on Databricks data security risks

Gain instant visibility to the type, sensitivity, and amount of PII data in your Databricks lakehouse.

Step 2: Identify user activities in Databricks

Obtain information on who has access to which sensitive data and remove unnecessary access.

Step 2: Identify user activities in Databricks

Obtain information on who has access to which sensitive data and remove unnecessary access.

Step 3: Find overexposed sensitive data

Identify who has access to PII and sensitive in your Databricks lakehouse and how much of that data is overexposed. Monitor and remove unnecessary access as needed.

Step 4: Tokenize sensitive PII in Databricks

Keep sensitive PII data functionalbut non-identifiable by replacing it with tokens and safeguard your data from breaches.

Step 4: Tokenize sensitive PII in Databricks

Keep sensitive PII data functionalbut non-identifiable by replacing it with tokens and safeguard your data from breaches.

Ready to see it yourself?

Getting started with Protecto is easy. Contact us to experience how Protecto can help you protect the privacy of your sensitive PII data in Databricks lakehouse for analytics and other critical workflows – all while simplifying and accelerating privacy compliance.
Book a demo

Easy Setup

  • Read-only access
  • Deploy as SaaS with no code setup
  • Pre-built Databricks connector
  • Non-intrusive & agentless

Identify and Classify PII

  • Find privacy risks and vulnerabilities
  • Discover overexposed personal data

Monitor activities & detect threats

  • Audit user permission and activities
  • Generate compliance reports

Sign up for a demo

Book a demo

Frequently asked questions

Data tokenization in Databricks Lakehouse refers to the process of replacing sensitive Personally Identifiable Information (PII) with randomly generated tokens. This technique helps protect the actual PII while enabling authorized users to work with tokenized data for analytics and processing.

Data tokenization enhances data security in Databricks Lakehouse by ensuring that sensitive PII is not stored in its original form. Instead, only tokens are stored, reducing the risk of data breaches and unauthorized access to sensitive information.
Yes, data tokenization is compliant with data protection regulations such as GDPR, CCPA, and HIPAA. By tokenizing PII, organizations can minimize the scope of sensitive data stored directly and improve their overall compliance data posture.

Absolutely. Tokenized data in Databricks Lakehouse can be used for data analysis, machine learning, and other processing tasks while preserving the privacy and security of the original PII.

Resources

Importance of Consistent Data Tokenization for Seamless Analytics

Learn the importance and need for consistently tokenizing sensitive data.
Read Blog

Discover PII and reduce millions of dollars in privacy risks

Global asset management company reduces millions of dollars in privacy risks within its Databricks cloud datastore and ensures data governance. Saves two months in migration to Azure by identifying unused data.
View Case Study

How Data Tokenization Plays an Effective Role in Data Security

Discover the many uses and importance of data tokenization.
Read Blog

Deliver privacy on Databricks in just a few clicks

We take privacy seriously.  While we promise not to sell your personal data, we may send product and company updates periodically. You can opt-out or make changes to our communication updates at any time.

Schedule a Call