Your company has a data warehouse that keeps your application information in BigQuery. The BigQuery data warehouse keeps 2 PBs of user data. Recently, your company expanded your user base to include EU users and needs to comply with these requirements:
✑ Your company must be able to delete all user account information upon user request.
✑ All EU user data must be stored in a single region specifically for EU users.
Which two actions should you take? (Choose two.)
To comply with the requirement to store all EU user data in a single region, you should create a dataset in the EU region specifically for EU users. This ensures all EU data is confined to a specific geographic location, meeting data residency obligations. To fulfill the requirement to delete all user account information upon user request, you can utilize DML statements in BigQuery. These statements allow you to perform updates and deletions on user records efficiently, enabling the company to respond to user data deletion requests as needed.
B and E is correct answer for me.
Second point "must be stored in a single region specifically for EU users " will achieve through option C only hence for me C and E is correct answer
Bigquery dataset can choose single region to store data, so B would be better
https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language The link above supports E since "delete all user account information upon user request" as per qn https://cloud.google.com/architecture/bigquery-data-warehouse: "A dataset is bound to a location. The dataset locations are as follows: Multi-regional: A large geographic area, such as the United States, that contains two or more geographic places." B is the other answer
B & E. Data is already stored in BigQuery, I do not see any reason to have anything to do with Cloud Storage. Also, BigQuery allows DML to do updates and deletes. So I would choose B & E
BE are correct sorry
B and E are the correct answer
Vote BE
Cloud Storage is out of scope !!
BD are correct
B and E are the correct answers. To comply with the requirements, you should create a dataset in the EU region that will keep information about EU users only. This will allow you to store all EU user data in a single region specifically for EU users. Additionally, you should use DML statements in BigQuery to update or delete user records based on their requests. This will allow you to delete all user account information upon user request as required.
D is not a good solution because re-uploading your data using a Cloud Dataflow pipeline is unnecessarily complex and does not address either of the requirements. Filtering user records out during the re-upload process does not allow you to store data in a specific region or delete data upon request.
C is not a good solution because creating a Cloud Storage bucket in the EU region does not address either of the requirements. A Cloud Storage bucket is simply a storage location, and it does not allow you to store data in a specific region or delete data upon request.
A is not a good solution because using BigQuery federated queries to query data from Cloud Storage does not address either of the requirements. Federated queries allow you to query data that is stored outside of BigQuery, such as in Cloud Storage, but they do not help you store data in a specific region or delete data upon request
Best option is BE.
B. Creating a separate dataset in the EU region for EU users allows your company to ensure that all data for these users is stored in a specific geographic location, complying with regional data residency requirements. BigQuery allows you to select the region where your dataset resides, and having a dedicated dataset for EU users makes it easier to manage and enforce policies specific to EU data. E. Using Data Manipulation Language (DML) statements in BigQuery (such as DELETE and UPDATE) enables your company to comply with requests to delete or modify user account information. This capability is essential for adhering to regulations like the GDPR, which may require companies to delete users' personal data upon request.
The two actions you should take are: B. Create a dataset in the EU region that will keep information about EU users only. This directly addresses the requirement to store EU user data in a single EU region. E. Use DML statements in BigQuery to update/delete user records based on their requests. This allows you to efficiently delete user account information upon request, fulfilling the GDPR requirement.
Here's why the other options are less suitable: A. Use BigQuery federated queries to query data from Cloud Storage: Federated queries are useful for accessing data in other sources, but they don't solve the problem of storing EU user data in a specific region or providing a mechanism for deleting user data. C. Create a Cloud Storage bucket in the EU region to store information for EU users only: While Cloud Storage can be used for data storage, it's not the primary data warehouse for your application. You'd need to manage data movement between BigQuery and Cloud Storage, which adds complexity. D. Re-upload your data using to a Cloud Dataflow pipeline by filtering your user records out: This is a time-consuming and potentially disruptive process. It's not the most efficient way to handle user data deletion requests.