Part ofProtection and Enforcement
Safe, Usable Data for Development and Testing
Replace sensitive values in copied databases and files while keeping the result useful for development, testing, analytics, and approved external work.
Why teams use static masking
Development and test teams need data that behaves like production. Giving them an exact production copy exposes sensitive information in environments where more people and tools may have access.
Static Data Masking replaces sensitive values before the target is delivered. Teams keep the structure, relationships, and formats their applications need, while the original values stay in production.
The same workflow can refresh database data and CSV, JSON, or XML files manually or on a schedule.
How static masking works
Choose the data teams need, replace sensitive values, and deliver a target that applications can still use.
Connect the database or file location, set the destination, and select the tables, columns, files, or paths the team needs.
Choose how each sensitive value should change and keep replacements consistent across related data.
DataSunrise masks values in batches, transfers the selected structure, and writes the protected target.
Review row counts, errors, task results, and reports before giving teams access or scheduling the next refresh.
The standard workflow leaves the production source unchanged.
Static masking capabilities
Protected data still has to work with the application. DataSunrise keeps replacements consistent across related tables and can carry table structure, constraints, indexes, and keys into the target.
Table Relations set the transfer order for connected records. Filters can also limit what moves by condition, row count, offset, or percentage, giving each environment the amount of data it needs.
The same task can prepare database tables and file data, so teams can manage both from one place.
Select the tables and columns the target needs. DataSunrise masks each protected field and transfers the selected structure to the target database.
Mask fields in CSV, JSON, and XML files across local paths, Amazon S3 and compatible storage, Azure Blob Containers and File Shares, or network storage. The target keeps the directory structure.
Sensitive Data Discovery finds sensitive content in additional document, image, archive, and data formats before teams decide how to handle it.
Run a masking task once or place it on a schedule to refresh protected environments as production data changes. Parallel processing and database-specific transfer methods can speed up larger jobs.
Each run records its status, row counts, and errors. Teams can review a PDF report or send results through a configured subscriber before releasing the dataset.
The standard workflow leaves the production source unchanged and writes masked data to a target database or file location. An in-place option is available for selected database designs.
Yes. Table Relations and consistent masking methods help preserve relationships while DataSunrise transfers related tables.
File Static Data Masking covers CSV, JSON, and XML.
Yes. Tasks can run manually or on a schedule, use parallel loading where available, and use database-specific transfer methods such as DirectPath, COPY, DBLink, BCP, or S3 loading.
No. Static masking changes data in a target dataset. Dynamic masking changes live results while stored values remain unchanged.
Map the right workflow
