Organizations are increasingly moving workloads into Databricks for its scalability, flexibility, cost savings, and performance. But moving sensitive data to the Cloud introduces the possibility of exposing data teams to new levels of risk – such as the misuse of sensitive data and violation of data regulations – making it challenging to manage and prepare sensitive data for data science and analytics.
For Databricks teams looking to unify data access governance for data science and BI, Immuta delivers automated security and privacy controls to safely analyze sensitive and protected data at scale.
How? Let us show you.
Join us for a webinar to learn more about how Immuta for Databricks enables you to safely unlock sensitive data.
We’ll show you:
- How Immuta for Databricks works
- Data-level security with fine-grained, attribute based access controls in Databricks
- Detailed auditing capabilities that prove compliant data access
- Unified data catalog with automated policies applied to Spark workloads in Databricks
You’ll also be among the first to see several new, highly-anticipated capabilities native to Databricks that will enhance collaboration and compliance in Databricks and enable data scientists to get self-service access to sensitive data in their preferred languages. This includes randomized response, open data science across R, Scala, Python & SQL, automated starter policies for major data regulations, and secure data collaboration..