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How To Automate Data Access Control Policies with Databricks and Immuta

For organizations that leverage Databricks for its best-in-class data analytics and AI capabilities, enabling self-service data access control across lakehouse architectures is critical for driving data initiatives and insights. But the decentralized nature of lakehouse architectures can easily become a barrier to secure, scalable data access. 

Databricks continues to innovate with centralized security and governance controls to enable more workloads across data warehouses and data lakes. As more data, users, and workloads are added, Immuta automates and orchestrates native controls to simplify managing access to Databricks and non-Databricks data sources. This helps reduce the common challenges data engineering teams face without automation, including having to translate requirements from governance teams, manually replicate anonymized data copies for PII and PHI, manage entitlements without any business context, and consistently enforce policies across their cloud data assets. 

Watch our on-demand webinar to find out how Immuta helps resolve these issues before they begin. You’ll learn:

  • Why current data use trends have outgrown traditional access control models.
  • How to effectively use access control automation to satisfy security and governance stakeholders unfamiliar with Databricks.
  • How Immuta’s modern and scalable access control models work seamlessly with Databricks to streamline sensitive data discovery, data access policy creation, enforcement, and auditing.
  • Examples of organizations that required a dynamic ABAC model to scale use of their sensitive data across Databricks.