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Google Exam Professional-Cloud-Architect Topic 1 Question 74 Discussion

Actual exam question for Google's Google Cloud Architect Professional exam
Question #: 74
Topic #: 1
[All Google Cloud Architect Professional Questions]

Your company has a Google Cloud project that uses BlgQuery for data warehousing There are some tables that contain personally identifiable information (PI!) Only the compliance team may access the PH. The other information in the tables must be available to the data science team. You want to minimize cost and the time it takes to assign appropriate access to the tables What should you do?

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Suggested Answer: C

This option can help minimize cost and time by using views and authorized datasets. Views are virtual tables defined by a SQL query that can exclude PII columns from the source tables. Views do not incur storage costs and do not duplicate data. Authorized datasets are datasets that have access to another dataset's data without granting direct access to individual users or groups. By creating a dataset for the data science team and creating views of tables that exclude PII, you can share only the relevant information with the team. By assigning an appropriate project-level IAM role to the members of the data science team, you can grant them access to the BigQuery service and resources. By assigning access controls to the dataset that contains the view, you can grant them access to query the views. By authorizing the view to access the source dataset, you can enable the view to read data from the source tables without exposing PII. The other options are not optimal for this scenario, because they either use materialized views instead of views, which incur storage costs and duplicate data (B, D), or do not create a separate dataset for the data science team, which makes it harder to manage access controls (A). Reference:

https://cloud.google.com/bigquery/docs/views

https://cloud.google.com/bigquery/docs/authorized-datasets


Contribute your Thoughts:

Eladia
6 months ago
Ah, but then you'd have to maintain those materialized views, which could get tricky. I'd rather go with the simpler option of regular views and just make sure the access controls are set up properly. Honestly, any of these options would probably work, as long as you're careful about the IAM roles and access permissions.
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Dana
6 months ago
Hmm, I'm not sure about that. Doesn't option B also cover the key steps, and it's a bit more concise? Creating materialized views instead of regular views might be a bit more efficient, especially if the data science team needs to query these tables frequently.
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Tammi
6 months ago
I agree, option C looks the most comprehensive. Creating a separate dataset for the data science team is a good way to isolate the PII-containing tables and maintain tight access controls. The only thing I'm not sure about is the need to authorize the view to access the source dataset - I wonder if that's strictly necessary if the view is already excluding the PII.
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Ernie
6 months ago
This question seems straightforward, but the details around access controls and authorizing views can get tricky. I'm leaning towards option C since it covers all the necessary steps, including creating a separate dataset for the data science team and authorizing the views to access the source data.
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Cora
5 months ago
Great, let's implement it
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Charlene
5 months ago
I agree, let's go with option C
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Emerson
5 months ago
It's definitely the most comprehensive option
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Caren
6 months ago
And authorizing the views to access the source data is important
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Merilyn
6 months ago
Creating a separate dataset for the data science team makes sense
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Jerry
6 months ago
Yeah, it covers all the steps we need to take
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Domonique
6 months ago
I think option C is the way to go
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