Privacera Enhances Data Access Governance for Google BigQuery, Starburst Enterprise, and Cloud Partner Ecosystem

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We are proud to announce the availability of Privacera Platform 6.3 and PrivaceraCloud 4.3. These new releases dramatically expand the Privacera Data Access Governance Platform’s ability to secure a diverse and increasing number of data sources and analytical workloads offered by leading public and third-party data platforms, such as BigQuery, Snowflake, AWS, and Starburst Enterprise. 

Enhanced Coverage and Data Masking for BigQuery

BigQuery, one of Google Cloud’s mainstays for analytics, is a fully-managed data warehouse designed to run analytics over vast amounts of data. Privacera Platform and SaaS releases include a comprehensive set of access control capabilities for BigQuery, empowering customers to define, manage, and enforce access control across projects, datasets, tables, columns, and views in BigQuery from a single, centralized location. 

Exhibit: Creating a column-level access policy that grants user Emily to only a few columns in the customer data table

Privacera also makes it easier to securely extract analytical insight from regulated data in BigQuery with the ability to filter data in rows. For example, if a table or view in BigQuery contains intermingled data for different organizations or regions, analysts will only be able to access data in rows that pertain to their specific departments or regions, ensuring that data is not viewed or used by unauthorized users. Privacera also provides column-level masking in a BigQuery table, empowering business analysts and data scientists with greater access to secured, sensitive data to unlock new analytical insights that would have otherwise been inaccessible for analysis. 

Exhibit: Creating a “row-level filter: customer data by country” policy to access data only from the UK.

New Tag-Based Access Controls in BigQuery

Tag-based policies play an important part in access governance programs. Built as a result of scanning enterprise data and classifying its sensitive elements, tag-based policies can manage data access based on labels that span across various departments, organizational groups, and resources. With this new release customers can build tag-based access control policies for BigQuery based on project, dataset, table or table view, as well mask sensitive data in single or multiple columns in the same or different tables. Tag-based policies provide administrators with a streamlined avenue to manage users’ access to data based on tags or labels. For example, administrators can build policies that specify data in a column as containing personally identifiable information, prohibiting it for use in marketing initiatives. Tags also ensure that even if data is moved or copied, user access is still enforced to prevent any unauthorized access or use.  

Additionally, access control policies can now be enforced based on data queries, resource-based masking policies, security zone, and tag-based policies to govern data access for fully managed PostgreSQL database in Google Cloud.

New Encryption Support in Starburst Enterprise

Privacera includes a new connector to encrypt data in Starburst Enterprise. Customers can now take advantage of the entire functionality of Privacera’s Unified Data Access Governance platform, including near-real time sensitive data discovery, fine-grained access control, and enterprise-grade encryption. With Privacera Encryption, organizations have the flexibility to encrypt data at the column level, rather than encrypting data in its entirety. This enables enterprises to accelerate and improve secure data sharing by automatically decrypting data for authorized users or applications when they access it. As a result, data science and analytics teams can utilize more data, build and refine predictive and machine learning models, and increase their accuracy by exploiting the full array of parameters in their organization’s data that have value in building predictive or machine learning models.

Privacera now also supports Starburst Enterprise to scan for sensitive data in MySQL, Oracle, and PostgreSQL.

Additionally, Privacera also deliver the following improvements and innovations across our cloud partner solutions:

  • Expanded Fine-Grained Access Control in Databricks – Enhanced support for fine-grained access control (FGAC) recently released in Databricks Runtime versions 10.4 LTS. 
  • Improved Performance and Scalability for Snowflake – Significant performance and scalability enhancements for Snowflake. Privacera PolicySync can now be deployed in platform and SaaS environments in minutes. New permissions for warehouse and tables have also been added. 
  • Enhanced Functionality for Attribute-Based Access Controls – Support for user and group attributes in EMR, Trino and Spark, Databricks Spark to filter rows based on user attributes.

See it in Action

If you are interested in seeing a live demo of Privacera in action, please visit www.privacera.com/demo-request.

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