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Google Exam Professional Data Engineer Topic 1 Question 67 Discussion

Actual exam question for Google's Professional Data Engineer exam
Question #: 67
Topic #: 1
[All Professional Data Engineer Questions]

You are preparing an organization-wide dataset. You need to preprocess customer data stored in a restricted bucket in Cloud Storage. The data will be used to create consumer analyses. You need to follow data privacy requirements, including protecting certain sensitive data elements, while also retaining all of the data for potential future use cases. What should you do?

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Suggested Answer: C

by Denise at Mar 22, 2023, 05:20 PM

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Avery
20 days ago
Honestly, I'm just hoping the correct answer isn't 'All of the above'. That would be a real head-scratcher!
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Dannie
1 months ago
Gotta love these data privacy questions! Option A sounds like a nice balance between masking sensitive info and keeping the full dataset. Not bad, not bad at all.
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Roy
23 hours ago
Using Dataflow and the Cloud Data Loss Prevention API seems like a solid approach.
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Patria
3 days ago
I agree, it's important to balance data privacy with retaining useful information.
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Craig
4 days ago
Option A sounds like a good choice. It masks sensitive data while keeping the full dataset.
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Monroe
2 months ago
Hmm, Option B might be the easiest solution, but I'm worried about potentially losing valuable data in the process. Better to err on the side of caution.
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Ettie
24 days ago
User 2: I agree, it's better to be cautious and not risk losing any valuable information.
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Nichelle
1 months ago
User 1: I think Option B is the safest choice to protect sensitive data.
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Diane
2 months ago
I'm leaning towards Option D. Handling the encryption at the storage level and using federated queries in BigQuery could be more efficient and secure.
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Tawna
5 days ago
Definitely. This approach can help protect sensitive data while retaining it for future use cases.
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Quiana
14 days ago
It's important to follow the principle of least privilege when sharing encryption keys.
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Jina
16 days ago
I agree. Using federated queries in BigQuery can also help maintain data privacy.
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Leila
26 days ago
Option D sounds like a good choice. Encrypting the data at the storage level is a secure approach.
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Melvin
2 months ago
Option C seems like the way to go. Encrypting the sensitive data while retaining the full dataset for future use is a smart approach.
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Lisha
2 months ago
That's a good point, but I still think option A is more secure in terms of protecting sensitive data elements.
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Flo
2 months ago
I disagree, I believe option B is better as it uses the Cloud Data Loss Prevention API and Dataflow to detect and remove sensitive fields.
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Lisha
2 months ago
I think option A is the best choice because it uses Dataflow and the Cloud Data Loss Prevention API to mask sensitive data.
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