Do you need rich test data to develop, test, or outsource your project? If so, you've probably tried either generating from scratch, or cloning 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). Data masking is an effective test data generation approach. 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 doc- umented tSQL script to modify, run, or schedule as your needs dictate.
Why Mask Your Test Data?
• Data Masking Beats Auto-Generating: According to Forrester Research Analyst Noel Yuhanna,
"90 percent of organizations prefer to mask data...[because creating test data]...is more complex and
doesn't always represent actual business scenarios."
• But My Test Data is Safe Because Only Internally Accessed: According to the Ponemon Institute,
"88% of all data breaches come from within; " thus, protecting your dev and test data is critically
Competitors: If MSSQL.DataMask does not fulfill your needs, then consider trying one of these more sophisticated products offered by other vendors:
1. The Data Masker
4. Grid Tools
5. Dynamic Data Masking / ActiveBase Security
6. Dataguise dgMasker
7. CalSQL (tSQL script)
8. Hexaware Akiva
9. IBM Magen
Notes / Articles:
Good reminder on the risks of anonymizing data (be thorough when scrubbing)
Good overview article on data sanitization reasons and techniques
Keywords: Personal Identifiable Information, Protected Health Information, Scrub Data, Substitute Data, Transform Data, Data Masking, Data Sanitization, Data Obfuscation, Data Security, Data Cleansing, Data Hiding, Hide Data, Disguise Data, Sanitize Data, Data Privacy, Health Insurance Portability and Accountability Act (HIPAA)