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While IT organizations in nearly all industries are under press to deliver new applications faster, those companies in regulated industries face an additional challenge. On one hand, development, testing, support, and reporting teams all need more and better test data sets. On the other hand, a variety of regulations (e.g. HIPAA, PCI-DSS, etc.) require these test data sets to be masked. Sensitive customer or patient data cannot be exposed to project teams, and compliance with data regulations increasingly comes with financial penalties. However, though many organizations feel the pressure to deploy data masking solutions, many of these project fail. It is estimated that as many as 50% of data masking projects will either fail outright, or else reach only limited success. The reason is simple: legacy masking products focus only on the creation of masked data copies, and not at all on distributing and updating these copies. Since source data changes often, any masking solution that cannot automate masked data delivery is unlikely to succeed. Since no legacy masking products solve this data delivery problem, the industry has seen only limited success and most customers express frustration with the cost, risk, and complexity of their masking solutions.
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