Anonymization

Privacy

Privacy matters in Software Development projects. But the reality is that it often gets treated as an afterthought. This then later on results in hastily put together scripts and/or tools that are separate from the main software, and therefore easily get overlooked and become out of sync. And that of course leads to errors/bugs that could cost an organization a lot in terms of money and/or reputation damage.

To address that undesirable situation Anonymization has been made an integral part of WYSE, ensuring a clean and uniform way of handling it and minimizing the 'forget' factor.

Be sure to check out the Trekkitopia demo as an "admin" to see a code example of anonymization.

Anonymization Rules

Privacy is implemented using anonymization rules. These rules are baked into the same (table and column) entities that form the heart of your application.

Arranging your anonymization is done per table by deleting rows and/or updating rows. The settings to control deletion and updating are database type specific. This allows you to fully capitalize on the various native delete and update capabilities of the various database types.

Per column you can supply expressions that determine the new, anonymized values. But since the selection of the rows involved is done on a table level only one update statement per table is created. All the columns that have update rules/expressions are combined into that one update. So no updating per row in the database. Depending on the number of rows in a table that can make a huge performance difference.