New Year Sale 2026! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions

Google Professional Data Engineer Exam - Topic 4 Question 12 Discussion

Actual exam question for Google's Professional Data Engineer exam
Question #: 12
Topic #: 4
[All Professional Data Engineer Questions]

You work for a global shipping company. You want to train a model on 40 TB of data to predict which ships in each geographic region are likely to cause delivery delays on any given day. The model will be based on multiple attributes collected from multiple sources. Telemetry data, including location in GeoJSON format, will be pulled from each ship and loaded every hour. You want to have a dashboard that shows how many and which ships are likely to cause delays within a region. You want to use a storage solution that has native functionality for prediction and geospatial processing. Which storage solution should you use?

Show Suggested Answer Hide Answer
Suggested Answer: A

Contribute your Thoughts:

0/2000 characters
Layla
4 months ago
Cloud Bigtable seems like a stretch for this kind of prediction.
upvoted 0 times
...
Mabel
4 months ago
Definitely leaning towards BigQuery for this use case.
upvoted 0 times
...
Albina
4 months ago
Wait, can BigQuery really handle 40 TB that fast?
upvoted 0 times
...
Eleonore
4 months ago
I think Cloud SQL could work too, but not as efficient.
upvoted 0 times
...
Xuan
5 months ago
BigQuery has great support for geospatial data!
upvoted 0 times
...
Huey
5 months ago
I recall that Cloud Datastore is more suited for NoSQL applications, so I doubt it would be the best choice here, especially with the need for predictions.
upvoted 0 times
...
Leota
5 months ago
I practiced a similar question where we had to choose a storage solution for real-time analytics. I think Cloud Bigtable could be useful, but I'm not confident about its geospatial processing.
upvoted 0 times
...
Frederic
5 months ago
I'm not entirely sure, but I think Cloud SQL for PostgreSQL could work too, especially with its geospatial extensions. But it might struggle with the scale of 40 TB.
upvoted 0 times
...
Rodney
5 months ago
I remember studying about BigQuery's capabilities for handling large datasets and its built-in machine learning features. It seems like a strong candidate for this scenario.
upvoted 0 times
...
Lawrence
5 months ago
Hmm, this looks like a tricky one. I'll need to carefully read through the options and think about which ones make sense if "Stop Rule Processing" is selected.
upvoted 0 times
...
Amber
5 months ago
This seems like a straightforward question about software usage and control. I'll carefully read through the options and think about what aspects of software deployment we can't control when downloading a package.
upvoted 0 times
...

Save Cancel