December 20

Anonymize streaming JSON payloads

New functionality was added to remove DIDs from Kafka-like streaming JSON payloads. Configuration information added as request metadata is used to control exactly how DIDs should be handled (ex., redact, mask, hash, realistic).

September 15

Web UI Improvements

The latest updatest to user interface are intended to make things easier. First, the project wizard will warn users if the project they are creating will overwrite existing tables in the selected destination connection. Second, filters were added to the runs page to allow users to filter the list by different facets.

August 22

Web UI Improvements

It's now easier than ever for enterprise customers to treat QID columns. A new option was added to the project wizard to set QID treatment for the entire project, saving time setting up anonymization projects for large databases.

July 26

Realistic replacement values for Direct Identifiers (DIDs)

Sometimes you don't want to mask or hash Direct Identifiers (DIDs) and want to have real looking, non-DID values. For example, you may need real looking phone numbers or email addresses in your anonymized datasets that aren't real. Starting today, you can replace DIDs with realistic values so your anonymized data looks real even though it isn't.

June 28

MySQL and SFTP data connectors

Data connector support for MySQL and Secure File Transfer Protocol (SFTP) is now available allowing users to connect to even more data store types.

Adjust column classifications

Allow users to adjust PII classifications assigned to columns through settings modal

May 18

S3 data connectors

Many customers store their data in Amazon Web Services (AWS) S3, typically in CSV and Parquet format. Today we introduce support for S3 when creating data connections. Users can connect to buckets stored in S3 to read in data and output anonymized data, just like connecting to a relational database.

Automatically treat new database tables

Engineering teams operating at velocity change their database schema often and add new tables during development. We introduced a feature to protect all new tables that are added to databases automatically. Enabling the "auto-create" datasets feature at the project level ensures that all new tables added to a database will be anonymized in the destination data store.

January 13

Deploy in your own Virtual Private Cloud (VPC)

Customers that want to keep data contained within their environment can deploy Privacy Dynamics within their Virtual Private Cloud (VPC). These cloud-prem installations can be done on AWS and GCP and require a managed Kubernetes service like EKS or GKE.