Of course, developers can generate synthetic data but that’s merely a far approximation.
Anonymization (strictly speaking “pseudonymization”) is an advanced technique that outputs data with relationships and properties as close to the real thing as possible, obscuring the sensitive parts and working across multiple systems, ensuring consistency.
1000’s of database tables and dozen of systems.
That’s where we come in with the CloverDX Data Anonymization Solution.
CloverDX Harvester is the first component in the solution. It crawls all your data (not just metadata structures) and scans for patterns representing sensitive information. The resulting map is a true and complete representation of occurences of sensitive information in your data.
Each piece of sensitive data can have its own rules and anonymization policy. This gives you fine control of the level of treatment required.
Based on the previous steps, we produce the second key component of the solution, the anonymization engine. It runs on top of the CloverDX Data Integration Platform, and can be re-generated easily upon changes. This engine has the policies built in and produces the anonymized copy of your production data on demand.
Holistic approach to anonymization produces resulting data set that's consistent among multiple dependent systems, making the anonymized data a reliable tool for development and testing of systems working in concert with each other.
We can combine anonymization with smart multi-pass generation and seeding of random data to ensure the strictest privacy requirements. You can balance how close you want to be to the original data against how anonymous the data needs to be.
Efficient discovery and learning algorithms allow templating and short implementation times for thousands of tables entering the anonymization scheme.
Once the Automated Anonymization Engine is built, you can create the anonymized data on demand, when you need it, as often you need it. It only takes a click of a button.