Google improves Data Security in BigQuery

Using Column based Data Masking in BigQuery and Data Catalog

Photo by Pierre Bamin on Unsplash

In my eyes, a great update that Google has released today for its SaaS Data Warehouse BigQuery: The Feature of Columns level masking of data. Because besides the challenges of processing Big Data, data security is also an issue that companies should, if not must, address. An example is the European DSGVO (learn more about it here).

Companies should therefore protect sensitive data, e.g. with encryption, to protect themselves from penalties and to protect their customers, employees, etc. One possibility is the pseudonomization or anomyzation of data — here is an interesting article on the subject (with phyton examples).

Anonymization vs. Pseudonymization — Image by Author

Other possibilities would be to use mechanisms, for example in your database like crambling. A possible approach for this would be to mix letters. Scrambling techniques like encryption and hashing or masking your data include hiding some information by using random characters or ****, for example. The implementation of the previously described functions could be seen as anonymization or pseudonymization. Here, it depends on who can cancel…