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

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?
A) Deploy the database using Cloud SQL.
B) Use BigQuery, and load data in batches.
C) C.Deploy the database using Bigtable.
D) Deploy the database using Cloud Spanner.

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?

Show Suggested Answer Hide 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
9 months ago
I agree, Bigtable seems like the best fit here!
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Dyan
9 months ago
Wait, can BigQuery really handle real-time data?
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Merilyn
10 months ago
Definitely not Cloud SQL, it can't handle that scale.
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Rolande
10 months ago
I think Cloud Spanner might be overkill for this use case.
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Dorothy
10 months ago
Bigtable is great for handling large volumes of semi-structured data!
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Shelba
10 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
11 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
11 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
11 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
11 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
11 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
11 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
11 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
11 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
11 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
1 year ago
Using Bigtable would definitely help with real-time monitoring and analysis of all that sensor data.
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Laquita
1 year ago
I agree, Bigtable is designed for massive scale and high throughput.
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Mozell
1 year 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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Junita
1 year ago
D) Deploy the database using Cloud Spanner.
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Reita
1 year ago
C) Deploy the database using Bigtable.
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Tamekia
1 year ago
B) Use BigQuery, and load data in batches.
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Jesusa
1 year ago
A) Deploy the database using Cloud SQL.
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Lanie
1 year ago
I'm leaning towards deploying the database using Cloud Spanner for better scalability and consistency.
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Norah
1 year ago
I disagree, I believe deploying the database using Bigtable would be a better option for real-time monitoring.
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Chauncey
1 year ago
I think we should use BigQuery and load data in batches.
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