Activity overview
Latest activity by danialcarter
Great discussion! These challenges are pretty common when teams start scaling their test environments. For data masking, Redgate's Classify → Map → Mask workflow is solid. One thing I'd add when setting up custom rules in Data Masker, make sure your masking is deterministic. This way, same input always produces same output across environments, which keeps referential integrity intact. For automation, CLI is your best friend here. Set up a pipeline where Redgate Clone snapshots your masked data, and then use a scheduler to auto-provision fresh environments for both Dev and QA. Once it's running, it saves enormous time. For GDPR compliance, regular audits are non-negotiable as Annabellelowe mentioned. But also maintain a clear data lineage log knowing exactly where sensitive data exists and how it's been masked gives you solid ground during any compliance review. One thing people often overlook documentation of your masking rules. Just like how a painting custom Baltimore professional keeps detailed records of every finish, coating, and surface prep for quality consistency, documenting your masking configurations ensures every environment is treated the same way and nothing slips through the cracks. Hope this helps, Zakary and anyone else facing similar issues! / comments
Great discussion! These challenges are pretty common when teams start scaling their test environments. For data masking, Redgate's Classify → Map → Mask workflow is solid. One thing I'd add when se...