Implementing basic masking rules
Figure 26: Basic workflow containing details on how to access all records in “Customers” tables using the model and connection string as provided. Records are masked using name and email anonymization
Proceed with changing American names to Swiss names. In order to do this you could use the tools from “BizDataX Country CH” section in the toolbox.
Figure 27: Toolbox items specific for Switzerland
To accommodate the gender-name relationship apply conditional activity from “BizDataX Branch&Distribute” section..
Figure 28: Toolbox items that support conditional masking
..on the FirstName field.
Figure 29: Conditional masking of FirstName field
Option: Add comments/annotations.
Figure 30: Rules and other workflow elements can be annotated
Last name masking does not require special handling according to gender.
Figure 31: Masking last names using BizDataX list of last names
Option: In addition to being able to annotate rules for better readability, you can also provide more transparency for business stakeholders by establishing links to policies and requirements defined in BizDataX Portal for the project. For example, links to policies can be imported to the toolbox.
Figure 32: Policy toolbox items that get created when BizDataX Portal project artefacts are imported
Here is how masking of names could look like:
Figure 33: Rules to anonymize name data
Use the following format to mask Email addresses;
”[first Swiss name].[last Swiss name]@email.com” as shown in the image below.
Figure 34: Email anonymization using text formula, current.FirstName and current.LastName are already changed
Another way of masking email addresses would be to simulate that not every customer has an email address. To accomplish that, we will use distributional branching. One branch could use masking activity as specified above and the other could be setting email to null. We could also specify what percentage of email addresses would be created and what percentage would be set to null.
Figure 35: Masking emails using distribution, text formula and setting to null, 50:50
We are now ready to build the demo project and run it from within the Visual Studio environment. Here is how results (could) look like:
Table 2: All sensitive data is anonymized. Demo completed!