The opportunity from opening up datasets is huge, but so are the risks. A possible data breach can cost a company its reputation and market share – as we saw happen to Target and Facebook.
On the other hand, few data-driven companies would like to pass on the opportunity of data monetization. Organizations find themselves caught in between these two seemingly conflicting strategies: innovating while assuring maximum security of their datasets.
Test data generation is another potential impediment to innovation, if done carelessly. Test systems are a notorious vulnerability point in enterprise architectures as the data is shared in the clear between development teams and data scientists. The only way to empower these teams and ensure secure operations is to protect test data sets.
In this session we review key enablers to achieving secure automated data monetization and test data generation.