Run analytics on your data while preserving privacy

Privacera’s Anonymization de-identifies any personal information, by replacing sensitive data with non sensitive data, resulting in continuous privacy and compliance without disrupting the use of data.

Why companies are moving to de-identify data?

Faced by rigorous privacy and compliance mandates. Companies are looking to de-identify sensitive information before storing and using it in the cloud.

Discover Discover

Privacera enables various forms of anonymization to enable data protection and preserve the privacy while maintaining referential integrity and analytical value of the data.

Simplify Data Protection and Privacy Compliance at Scale

Enable Data for Analytical Use

Enable safe consumption and analytics of data while preserving privacy and enabling protection of data in the cloud.

Control access to de-identified data

Privacera enables centralized policies to control which users can re-identify data. Privacera provides UDFs and APIs to enable seamless re-identification on demand.

Achieve Compliance

Meet stringent compliance, privacy, and regulatory requirements including GDPR, CCPA, PCI, HIPAA, and PII mandates.

Why Privacera Anonymization?

Preserve analytical insights and privacy

Privacera Anonymization can preserve the referential and statistical integrity of data when the data is anonymized. IT teams can use their data for analytics and ML while compliance and privacy is data is maintained even if the data is copied.

Built for Cloud

Privacera Anonymization is deeply integrated with ETL and data consumption tools, and can provide performance efficient enforcement across the cloud datastores. Privacera anonymization can be run as a micro services and integrated into the DevOps workflows.

Centralized key management and policies

Privacera’s leverages Ranger key management to store keys and enable fine grain policies at user or group level. Privacera key management is also integrated with popular cloud key vaults.

Frequently Asked Questions

When is difference between field encryption and masking?

Encryption uses key and an algorithm to create random pseudo characters for a given value. Encrypted values can be reversed based onthe key available and applying a decryption algorithm. Encryption can be used when data needs to be protected at rest and in use, while enabling certain users to reverse the encryption and get original data back. Masking is typically one-way and not reversible. Masking can be used to remove PII data altogether.

Can data be anonymized as part of data ingest?

Privacera has in built integration with Kafka, Ni-Fi, Streamsets and can help anonymize data as the data is being ingested.

Can the encryption keys be stored in an external key store?

Privacera can store keys in an external HSM or cloud based key vaults.

Resources & Latest News


Security and Privacy for modern data platforms

This paper walks through how security and privacy can be enabled for big data and cloud environments using Privacera.


Privacera solution for AWS EMR

Use this link for request a docker package to install Apache Ranger based fine grained access control solution for AWS EMR

Interested in seeing Anonymization in Action?