Works on: Windows 10 | Windows 8.1 | Windows 8 | Windows 7 | Windows XP | Windows 2000 | Windows 2003 | Windows 2008 | Windows Vista | Windows 2012 SHA1 Hash: 8ed8c4f80751cd7e6be7fe6f9ef79e7782b8bcaa Size: 256.81 KB File Format: zip
Rating: 2.04347826
out of 5
based on 23 user ratings
Downloads: 172 License: Free
MSSQL.DataMask is a free software by WinTestGear and works on Windows 10, Windows 8.1, Windows 8, Windows 7, Windows XP, Windows 2000, Windows 2003, Windows 2008, Windows Vista, Windows 2012.
You can download MSSQL.DataMask which is 256.81 KB in size and belongs to the software category Lockdown. MSSQL.DataMask was released on 2010-05-13 and last updated on our database on 2017-04-22 and is currently at version 1.
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MSSQL.DataMask Description
Do you need rich test data to develop, test, or outsource your project? If so, youve probably tried either generating from scratch, or cloning from production data. Auto-generating the test data is difficult and error prone for all but the simplest databases due to complex variances, frequencies, and data interdependencies. Business and legal obligations such as HIPAA require that production data clones be thoroughly sanitized (masked) of personal indentifiable information (PII) and/or protected health information (PHI). MSSQL.DataMask is a free, simple tool that quickly sanitizes a clone of your production database into a safe, secure test database. Once built, the process is easily repeatable to refresh your test data from production. You can either load and re-run a set of data masks from the application, or generate a fully documented tSQL script to modify, run, or schedule as your needs dictate. Why mask your test data? Ã??? Creating test data is more complex and doesnt always represent actual business scenarios versus masking (anonymizing) production data Ã??? Most data breaches come from within an organization; thus, protecting your dev and test data is critically important. There are three categories of datamasks: 1. Scrub: Overwrite all rows of a column with the "same value" 2. Substitute: Overwrite all rows of a column with a new "unique value" 3. Transform: Overwrite all rows of a column with an "obsfucated original value".