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Google Professional Data Engineer Exam - Topic 6 Question 69 Discussion

What are two of the benefits of using denormalized data structures in BigQuery?
C) Reduces the amount of storage required, increases query speed
A) Reduces the amount of data processed, reduces the amount of storage required
B) Increases query speed, makes queries simpler
D) Reduces the amount of data processed, increases query speed

Google Professional Data Engineer Exam - Topic 6 Question 69 Discussion

Actual exam question for Google's Professional Data Engineer exam
Question #: 69
Topic #: 6
[All Professional Data Engineer Questions]

What are two of the benefits of using denormalized data structures in BigQuery?

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Suggested Answer: C

by Tegan at Apr 19, 2023, 11:02 PM

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Coral
9 months ago
Not sure about A, isn't it risky to reduce data too much?
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Rosalind
9 months ago
Wait, can denormalization really speed things up? Sounds too good to be true!
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Yuette
9 months ago
I agree with D, faster queries are always better.
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Shannon
9 months ago
I think C is also a good point. Storage matters!
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Cordell
9 months ago
Definitely A and B! Less data processed is a win.
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Nell
9 months ago
I’m leaning towards option D because it mentions both reducing data processed and increasing speed, which sounds right based on what we studied.
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Stefania
9 months ago
I feel like denormalization simplifies queries too, but I can't recall if that's one of the main benefits listed in our notes.
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Walton
9 months ago
I remember practicing a question that mentioned reducing the amount of data processed, which seems relevant here.
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Elise
10 months ago
I think one of the benefits is definitely increasing query speed, but I'm not sure about the other one.
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Malcom
10 months ago
Ah, I remember learning about this in class. The Release phase list should have all the critical steps, from initial planning to final deployment. I'm pretty confident I can narrow this down to the right answer.
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Blondell
10 months ago
This is a good question to test our knowledge of loan administration. I'll methodically go through each option and think about which ones are most likely to be obtained routinely after the loan is funded.
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Curt
10 months ago
I'm pretty confident I know the right answer here. Splitting the data 50/50 between training and testing is a common and reliable approach.
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Roslyn
1 year ago
Wait, so denormalization is like the BigQuery version of a cheat code? Sign me up!
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Elizabeth
1 year ago
D) Reduces the amount of data processed, increases query speed
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Irma
1 year ago
C) Reduces the amount of storage required, increases query speed
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Micah
1 year ago
A) Reduces the amount of data processed, reduces the amount of storage required
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Blossom
1 year ago
Option D is close, but I think C is the better answer. Reducing data processed and increasing speed - that's the sweet spot for denormalization.
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Hui
1 year ago
Hmm, I'm not sure I fully understand the benefits of denormalization. But hey, at least it's not as confusing as trying to figure out the optimal number of shards in a BigQuery table!
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Bok
1 year ago
Yeah, denormalization can definitely help with reducing storage and speeding up queries.
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Diane
1 year ago
C) Reduces the amount of storage required, increases query speed
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Jamal
1 year ago
Hmm, I'm not sure I fully understand the benefits of denormalization. But hey, at least it's not as confusing as trying to figure out the optimal number of shards in a BigQuery table!
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Jaime
1 year ago
A) Reduces the amount of data processed, reduces the amount of storage required
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Gayla
1 year ago
C) Reduces the amount of storage required, increases query speed
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Tula
1 year ago
A) Reduces the amount of data processed, reduces the amount of storage required
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Carin
1 year ago
I agree, C is the way to go. Denormalized data structures are all about trading off storage for speed, and that's exactly what this question is asking about.
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Erasmo
1 year ago
Definitely, it's important to understand the benefits of denormalized data structures in BigQuery.
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Rosenda
1 year ago
Yes, denormalized data structures are all about that trade-off.
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Ruthann
1 year ago
I think C is the correct answer. It reduces storage and increases query speed.
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Levi
1 year ago
So, the benefits are reducing data processed and increasing query speed.
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Bernardo
1 year ago
Option C seems like the most comprehensive answer. Denormalization can definitely reduce storage requirements and improve query performance.
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Georgiann
1 year ago
Yes, denormalized data structures in BigQuery can definitely improve performance and reduce storage needs.
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Rosendo
1 year ago
I agree, denormalization can really help with reducing storage and speeding up queries.
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Reid
1 year ago
Yes, that's true. It also increases query speed.
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Levi
1 year ago
I think using denormalized data structures in BigQuery can reduce the amount of data processed.
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