IBM InfoSphere Optim Data Privacy Features

Meets GDPR requirements for pseudonymisation under the Data Protection by Design and by Default requirements. 25 reviewers of IBM InfoSphere Optim Data Privacy have provided feedback on this feature.

Meets de-identification requirements under the CCPA. 25 reviewers of IBM InfoSphere Optim Data Privacy have provided feedback on this feature.

Offers traditional static de-identification (also known as consistent replacement), where the pseudonymized data uses the same pseudonyms across multiple data sets. For example, John Smith is replaced with Robert Fox and the Robert Fox name is used multiple times. This type of pseudonymization carries some risks of re-identification if paired with enough datasets. 25 reviewers of IBM InfoSphere Optim Data Privacy have provided feedback on this feature.

Offers dynamic de-identification (also known as random replacement), where the pseudonymized data uses different pseudonyms across multiple data sets. For example, John Smith is replaced with Robert Fox once, and then the next time the data is used the name changes to Michael Jones. This type of pseudonymization carries lesser risk of re-identification if paired with many datasets. 24 reviewers of IBM InfoSphere Optim Data Privacy have provided feedback on this feature.

As reported in 25 IBM InfoSphere Optim Data Privacy reviews. Offers methods to de-identify large volumes of data using batch files.

Connects to mobile platforms using a mobile SDK. 23 reviewers of IBM InfoSphere Optim Data Privacy have provided feedback on this feature.

Based on 25 IBM InfoSphere Optim Data Privacy reviews. Offers APIs to connect products.