Webinar Description
Key Takeaways
- Examines limitations of native data masking in Snowflake and Databricks, which mask data at the presentation layer without altering underlying stored data.
- Addresses compliance risks and data exposure when native masking fails to maintain data relationships across environments.
- Covers enterprise-grade masking strategies for analytics sources exceeding 10TB.
- Designed for data security professionals, compliance officers, and analytics platform architects in regulated industries.
Native Masking Limitations in Analytics Platforms
Organizations deploying Snowflake and Databricks for large-scale analytics often rely on native data masking features to protect sensitive information. However, these built-in capabilities operate only at the presentation layer, leaving the underlying stored data unchanged. This architectural limitation creates gaps in data protection, particularly when masked data must maintain referential integrity across multiple environments used for development and testing.
The webinar explores how presentation-layer masking can lead to compliance failures when sensitive data remains accessible in its original form within the platform. For organizations handling analytics workloads at scale, these limitations compound as data volumes grow and governance requirements become more complex.
Enterprise Data Masking at Scale
Perforce Delphix experts lead this session, focusing on masking strategies that address analytics sources exceeding 10TB. The discussion covers approaches to irreversible masking that protect data across development, testing, and analytics use cases while preserving data relationships necessary for functional environments.
Key topics include data privacy, data governance, and maintaining compliance when working with sensitive information in analytics platforms. The session demonstrates how enterprise-grade masking differs from native platform features in scope and effectiveness.
Who Should Attend
This webinar is relevant for data security professionals, compliance officers, data engineers, and analytics platform architects working in mid to large enterprises. Organizations in regulated industries currently using or evaluating Snowflake and Databricks will find the content particularly applicable to their data governance and privacy requirements.