Topic 1 Question 109
You are working at a sports association whose members range in age from 8 to 30. The association collects a large amount of health data, such as sustained injuries. You are storing this data in BigQuery. Current legislation requires you to delete such information upon request of the subject. You want to design a solution that can accommodate such a request. What should you do?
Use a unique identifier for each individual. Upon a deletion request, delete all rows from BigQuery with this identifier.
When ingesting new data in BigQuery, run the data through the Data Loss Prevention (DLP) API to identify any personal information. As part of the DLP scan, save the result to Data Catalog. Upon a deletion request, query Data Catalog to find the column with personal information.
Create a BigQuery view over the table that contains all data. Upon a deletion request, exclude the rows that affect the subject's data from this view. Use this view instead of the source table for all analysis tasks.
Use a unique identifier for each individual. Upon a deletion request, overwrite the column with the unique identifier with a salted SHA256 of its value.
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According to me, the question states "The association collects a large amount of health data, such as sustained injuries." and the nuance on the word such => " Current legislation requires you to delete "SUCH" information upon request of the subject. " So from that point of view the question is not to delete the entire user records but specific data related to personal health data. With DLP you can use InfoTypes and InfoType detectors to specifically scan for those entries and how to act upon them (link https://cloud.google.com/dlp/docs/concepts-infotypes) I would say B.
👍 67milan742021/07/09IMHO a) is the correct answer because it is easier to operate. The question is not how to mask data and so on but just to delete data on request, so I don't think that we have to use for just the deletion of specific data DLP.
👍 31XDevX2021/06/30Answer is A. Use a unique identifier for each individual. Upon a deletion request, delete all rows from BigQuery with this identifier.
Using a unique identifier for each individual allows you to easily identify and delete the data of a specific person when a request is made. You can then simply delete all rows from BigQuery that contain this identifier to fulfill the request.
Option B, running the data through the Data Loss Prevention (DLP) API to identify any personal information and saving the result to Data Catalog, is not a recommended approach. While the DLP API can be used to identify personal information in data, it is not necessary for this specific task. Additionally, saving the result to Data Catalog would not enable you to delete the data from BigQuery.
👍 6omermahgoub2022/12/22
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