The Partnership Provides Automated Data Security, Privacy Protection and Compliance for Analytics and Machine Learning on Sensitive Datasets
Immuta, the automated data governance company, announced a partnership with Databricks, the leader in Unified Data Analytics. The joint solution empowers data teams to perform analytics on sensitive data in the cloud in a compliant, policy-driven, and automated way. Through a new, native integration, the two companies help customers make data secure, anonymized and compliant for cloud analytics and machine learning.
Immuta and Databricks partner to deliver automated data security, privacy protection and compliance on sensitive data sets
With Databricks and Immuta, customers can enforce fine-grained access controls and dynamically apply anonymization techniques from directly within Databricks and Delta Lake, the open source storage layer that brings reliability to data lakes. As a result, Databricks users see only what they’re allowed to see, based on who they are, and their approved purpose. This enables organizations to securely access data and build machine learning models.
“Databricks helps data teams perform advanced analytics and develop machine learning models on the entire data lake. Working with sensitive data and governance of that data has to be ‘always on,’” said Pankaj Dugar, vice president of ISV and Technology Partners, Databricks. “This partnership with Immuta allows our customers to enforce governance directly in the Databricks environment in a truly native, frictionless way that doesn’t require lengthy compliance reviews or the copying, extracting, and manual anonymization of analytics data.”
Additional benefits of the joint solution include:
- Frictionless data governance policy enforcement: Immuta’s data controls are non-invasive and invisible to Databricks users.
- Immuta’s self-service data catalog enables Databricks users and teams to easily and securely subscribe to data based on policy logic.
- Always-on, data policy enforcement includes row-level filtering as well as column- and cell-level masking.
- Purpose-based data access and anonymization, which is critical for compliance with regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA).
- Automated application of policies on data based on metadata or ontologies placed on the data, rather table- or column-based policies.
“Without an automated approach to data governance, companies often find themselves in an ‘all or nothing’ situation when provisioning data for analytic workloads creating real security and compliance risks for the business,” said Rob Lancaster, GM, Cloud, Immuta. “With our latest Databricks integration, we’ve made data governance in the cloud a frictionless, always-on, always-enforced service. As a result, time-to-data is dropped from days or weeks to seconds significantly increasing the speed of analytics and model development while ensuring outputs are legal and ethical.”