Google Professional Cloud Database Engineer Exam - Topic 5 Question 28 Discussion

Actual exam question for Google's Professional Cloud Database Engineer exam

Question #: 28
Topic #: 5

[All Professional Cloud Database Engineer Questions]

You want to migrate an existing on-premises application to Google Cloud. Your application supports semi-structured data ingested from 100,000 sensors, and each sensor sends 10 readings per second from manufacturing plants. You need to make this data available for real-time monitoring and analysis. What should you do?

ADeploy the database using Cloud SQL.

BUse BigQuery, and load data in batches.

CC.Deploy the database using Bigtable.

DDeploy the database using Cloud Spanner.

Show Suggested Answer

Suggested Answer: A

https://cloud.google.com/spanner/docs/iam?hl=it

by Sheron at Mar 21, 2024, 12:25 PM

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Vanesa

6 months ago

I agree, Bigtable seems like the best fit here!

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Dyan

6 months ago

Wait, can BigQuery really handle real-time data?

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Merilyn

6 months ago

Definitely not Cloud SQL, it can't handle that scale.

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Rolande

7 months ago

I think Cloud Spanner might be overkill for this use case.

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Dorothy

7 months ago

Bigtable is great for handling large volumes of semi-structured data!

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Shelba

7 months ago

Cloud Spanner sounds appealing because it’s scalable and supports real-time data, but I’m worried about the complexity of managing it.

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Lili

7 months ago

I feel like Bigtable could be a good choice since it’s designed for high throughput and low latency, but I’m not completely certain.

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Cassie

7 months ago

I think BigQuery is great for analytics, but it’s more about batch processing, right? Not sure if it’s the best fit for real-time needs.

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Charolette

8 months ago

I remember we discussed that Cloud SQL might not handle the scale of 100,000 sensors effectively, so I’m leaning away from that option.

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Sherrell

8 months ago

I feel pretty confident about this one. Based on the requirements, I would go with option D and deploy the database using Cloud Spanner. It's designed for high-throughput, low-latency applications, which seems perfect for this use case.

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Elza

8 months ago

Okay, let me think this through. We need to handle a huge amount of data from 100,000 sensors, with 10 readings per second. That's a lot of data! I think the key here is to find a solution that can ingest and process this data in real-time, so I'm leaning towards option B with BigQuery.

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Aliza

8 months ago

Hmm, I'm a bit unsure about this one. The question mentions real-time monitoring and analysis, so I'm not sure if Bigtable is the best fit. Maybe I should look into the other options as well, like BigQuery or Cloud Spanner.

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Leigha

8 months ago

This seems like a pretty straightforward question. I'd go with option C and deploy the database using Bigtable. It's designed for handling large volumes of semi-structured data, which is exactly what we need here.

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Graciela

8 months ago

Hmm, I'm a bit confused. Increasing the network bandwidth to 2 Gbps or 10 Gbps seems like a lot of work. I'm leaning towards keeping the 1 Gbps link and doing an offline migration.

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Thomasena

8 months ago

I'm pretty confident I know the answer to this one. The EnterpriseOne Server Manager Console is certified to run on Linux, Windows, and IBM System I.

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Daniela

1 year ago

Wow, 100,000 sensors? That's a lot of data! I hope the person who has to manage that infrastructure gets paid well. Bigtable seems like the right choice to handle all that semi-structured goodness.

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Novella

1 year ago

If I had a 100,000 sensors sending data at 10 readings per second, I'd be tempted to just use a rubber band and a paper clip to collect it all. But in all seriousness, Bigtable sounds like the way to go here.

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Marguerita

11 months ago

Using Bigtable would definitely help with real-time monitoring and analysis of all that sensor data.

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Laquita

11 months ago

I agree, Bigtable is designed for massive scale and high throughput.

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Mozell

12 months ago

Bigtable sounds like a good option for handling that amount of data.

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Darell

1 year ago

Cloud Spanner might be overkill for this use case. I'd stick with a NoSQL solution like Bigtable to handle the high throughput and semi-structured data.

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Tina

1 year ago

I'd go with Bigtable. It's designed for handling large-scale, semi-structured data, and it can provide the real-time performance you need for monitoring.

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Ocie

1 year ago

BigQuery seems like the best option here. Dealing with semi-structured data from so many sensors and requiring real-time monitoring is a perfect use case for a data warehouse like BigQuery.

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