Data Anonymization

What is data anonymization?

Data anonymization is the process of protecting private or sensitive data by altering or removing personally identifiable information (PII) from it. The data anonymization process allows insights from the data to be used while protecting users’ privacy and sensitive information.

With the recent increase of collected and stored data across industries, anonymized data has become a crucial process for preserving trust and authority in organizations and complying with data protection regulations.

Example: For our annual survey, we use data anonymization techniques to protect customers’ privacy while showcasing key industry insights. 

What are some data anonymization techniques?

There are a variety of methods and techniques used to create anonymous data. These include data masking, where a realistic yet synthetic data set is created that mimics the original set’s characteristics and patterns; data swapping, where specific dataset attribute values are exchanged between different records, and data shuffling, where data points within a set of data are randomly rearranged. 

Data anonymization tools can be used to help automate and streamline this process for greater efficiency.