Multi-stage big data analytics pipelines enable users to build data preparation or analytics workbooks on top of secure data views, and apply policies at every stage of the pipeline from ingest to export. Secure big data views enable administrators and privileged users to expose a subset of fields to specific groups of users, and apply masking and anonymization (or aggregation) to sensitive data fields, while leveraging column-level security of Datameer and external systems. This ensures all users are always working from a single standard source of truth.
With authentication, authorization and encryption capabilities, Datameer’s robust role-based security features ensure you can combat potential fraud, and protect personally identifiable information. Masking big data is easy with secure hash, MD5 and randomization functions.
Data lineage allows you to visually understand and track every step that led to your final result, from initial data ingest, across joins and through every single transformation. Understand who did what, and when. Audit logs capture every login, change of permissions and other privileged actions that might involve sensitive data.
Manage your big data retention policy with Datameer's flexible data retirement rules. For each imported data set, an individual set of rules can easily be configured to keep data permanently, or purge records that are older than a specific time window. Security rules allow retired data to be either instantly removed, retained until a specified time, or manually removed after system administrator approval.
While the Hadoop ecosystem evolves and big data governance standards and technologies emerge, Datameer gives you the rigorous big data governance you need right now, with a pluggable architecture and open APIs that protect your investment as new systems and standards are introduced.