BigID and Alation have partnered to enable customers to scale data discovery across the enterprise for dynamic, cohesive data governance, and bridge privacy compliance policies, business knowledge, and automated data insights for self-service governance.
Customers can leverage BigID’s discovery foundation with the Alation Data Catalog: discovering, tagging and mapping sensitive and regulated data for accelerated governance.
Together, BigID and Alation enable CDOs, data stewards, and analytics teams to understand which policies apply to which data sets across their infrastructure—based on privacy regulations, internal policies, and the relationship of the data to the data subject or consumer.
Privacy, data stewardship, and analytics teams can leverage BigID’s discovery and inventory foundation across all enterprise data sources with Alation’s data curation capabilities to:
- Discover, tag, and map sensitive and regulated data to automate governance at the point of consumption
- Automatically identify personal information for privacy and data stewardship teams
- Gain visibility into which policies apply to specific data sets across a complex data ecosystem
- Apply tags derived from Alation data curation to the mapped data elements in the inventory across structured and unstructured data sources
- Automatically surface new findings from BigID to allow for policies to be automatically assigned in the Alation interface
- Eliminate manual steps in identifying and tagging entity identification data and improving accuracy
Teams now have a consistent foundation to enable collaboration with the integration of Alation’s unified interface and BigID’s unified data inventory. In addition, the BigID unified data inventory eliminates data silos and ensures that the catalog is dynamically updated for ongoing data stewardship.
Users now gain visibility into which policies apply to specific data sets across a complex data ecosystem, eliminating manual steps in identifying and tagging entity identification data and improving accuracy beyond technical metadata alone. Moreover, self-service analytics users can be guided through privacy-aware data consumption.