Snowflake and Securiti Partnership Enables Data Innovation at Scale

Securiti accurately finds all sensitive data, then orchestrates Snowflake’s dynamic data masking policies directly from Securiti’s unified DataAI Command Platform into Snowflake for local enforcement.  Securiti’s modular, API-driven architecture lets customers find and mask sensitive data based on attributes, ensuring data teams can access the data they need without compromising security and privacy controls.

Expand Controls and Avoid Silos for Scaled Snowflake

Technical challenges and considerations for maximizing the value of large-scale Snowflake deployments include scalability, storage, governance, and integration. Securiti’s DataAI Command Platform^TM address these unique concerns for customers who have scaled their Snowflake footprint across multiple lines of business.

In addition to building the right pipelines to make the right data accessible to the right end users, large Snowflake implementations also need to address the following:

• Data Security and Compliance
  Most organizations have multiple lines of business and a hybrid data landscape with data dispersed across multiple regions. When each organization interprets and codes policy individually (siloes), data management drift occurs, negatively impacting data accuracy and trust.Using Securiti’s DataAI Command Platform^TM Services, Snowflake customers can:
  • Manage user access controls, roles, and permissions to prevent unauthorized access
  • Implement secure data access policies by orchestrating sensitive data masking at scale
  • Improve data security posture by hardening configuration settings
  • Comply with global data regulations (e.g., GDPR, CCPA) and govern cross-border data transfers when deploying across multiple regions
• Data Integration and ETL
  • Customers want to combine streaming and batch data to create better real-time customer experiences and innovate new products.  Securiti can remove bottlenecks for Snowflake customers by finding sensitive data as it is staged and ingested from various sources and formats.
  • Securiti’s lineage and labeling services can help address tracing data transformation, cleansing, and enrichment requirements across multiple Snowflake datasets.
  • Snowflake customers can leverage Securiti’s efficient data pipeline orchestration and monitoring to remediate, notify and address any sensitive data or unwanted new sensitive data being imported from third parties.
• Multi-Region Deployment and Data Sovereignty
  Customers can improve user experience across regions by using Securiti’s DataAI Command Platform^TM as the unified DataAI Command Platform for protecting sensitive information when replicating and synchronizing data across regions through multiple Snowflake accounts.
• Data Retention: Continuously Updated and Audited
  Efficient storage and retrieval combined with improved query performance are key concerns for Snowflake data storage and management.  Another area in data storage and management is the data retention policy.  Securiti can identify sensitive data and apply the correct data retention policies through labels.

Conclusion

By leveraging the technical features of both platforms, organizations can enjoy the benefits of cutting-edge data management while maintaining the highest levels of security and compliance. For large-scale implementations, Securiti orchestrates and extends the benefits of Snowflake's data management and controls across multi-region, multi-account deployments. To discuss how to improve decision-making and drive data innovation in Snowflake, request a meeting with Securiti’s Snowflake experts now.