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Google Professional Data Engineer Exam - Topic 2 Question 63 Discussion

You need ads data to serve Al models and historical data tor analytics longtail and outlier data points need to be identified You want to cleanse the data n near-reel time before running it through Al models What should you do?
A) Use BigQuery to ingest prepare and then analyze the data and then run queries to create views
B) Use Cloud Storage as a data warehouse shell scripts tor processing, and BigQuery to create views tor desired datasets
C) Use Dataflow to identity longtail and outber data points programmatically with BigQuery as a sink
D) Use Cloud Composer to identify longtail and outlier data points, and then output a usable dataset to BigQuery

Google Professional Data Engineer Exam - Topic 2 Question 63 Discussion

Actual exam question for Google's Professional Data Engineer exam
Question #: 63
Topic #: 2
[All Professional Data Engineer Questions]

You need ads data to serve Al models and historical data tor analytics longtail and outlier data points need to be identified You want to cleanse the data n near-reel time before running it through Al models What should you do?

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Suggested Answer: A

by Thurman at Dec 29, 2022, 08:52 AM

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Delfina
10 months ago
Definitely need to cleanse data in near-real time for accurate models!
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Roxanne
10 months ago
Wait, can Cloud Composer really handle that efficiently?
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Thaddeus
10 months ago
Cloud Composer seems a bit overkill for this task.
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Shizue
11 months ago
I think Dataflow is the best option for identifying outliers.
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Apolonia
11 months ago
BigQuery is great for analyzing large datasets quickly.
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Ivette
11 months ago
I’m leaning towards option C with Dataflow, but I’m a bit uncertain if it’s the most efficient way to cleanse data before running AI models.
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Chaya
11 months ago
I feel like using BigQuery directly for analysis is a solid choice, but I’m not clear on how it handles cleansing in near-real time.
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Audrie
11 months ago
I remember practicing a question similar to this, and I think Cloud Composer could be useful for orchestrating the workflow, but I’m not confident about its real-time capabilities.
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Precious
11 months ago
I think using Dataflow might be the best option for identifying longtail and outlier data points, but I'm not entirely sure how it integrates with BigQuery.
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Brigette
11 months ago
Okay, I've got a plan. First, I'll insert the slides from the Campus presentation into the Documents folder. Then I'll make sure slide 6 is "Discover Your Campus" and slide 7 is "Display Your Art". Should be doable!
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Reed
11 months ago
Okay, I've got this. The sequence is Discover, Offer, Request, Acknowledgement. The client first discovers the DHCP server, then the server offers an IP address, the client requests that address, and the server acknowledges it.
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Cecil
11 months ago
I'm a little confused by all the different Citrix products and features mentioned here. I'll need to review my notes to make sure I understand the correct redundancy options for the License Server.
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