Audience: All Immuta users
Content Summary: This section highlights the benefits and deployment methods of Immuta and details the data access patterns: Databricks, HDFS, Presto, S3, S3 Access in Spark and Databricks, Snowflake, Spark, and SQL. Spark, and SQL.
Immuta provides a consistent point of access for all data analysis and dynamically protects your data with complex policies -- enforced based on the user accessing the data and the logic of the policy -- creating efficient digital data exchanges compliant with organizations' regulations with complete visibility of policy enforcement.
- Unification: All your data remains in-place; however, it is virtually unified within Immuta for a single point of access.
- Data Policies: Data is hidden, masked, redacted, and anonymized in the control plane based on the attributes of the users accessing the data and the purpose under which they are acting.
- Authoritative Virtual Data Sources: Complex joins and data transformations can be exposed in Immuta as authoritative virtual data sources for downstream users.
- Audit Consistency: All activities are audited in a consistent manner across data silos from within the virtual layer. This simplifies audit log analysis and increases the richness of audit logs.