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Google Professional Data Engineer Exam - Topic 1 Question 54 Discussion

You are building a data pipeline on Google Cloud. You need to prepare data using a casual method for amachine-learning process. You want to support a logistic regression model. You also need to monitor andadjust for null values, which must remain real-valued and cannot be removed. What should you do?
C) Use Cloud Dataflow to find null values in sample source data. Convert all nulls to 'none' using a Cloud Dataprep job.
A) Use Cloud Dataprep to find null values in sample source data. Convert all nulls to 'none' using a Cloud Dataproc job.
B) Use Cloud Dataprep to find null values in sample source data. Convert all nulls to 0 using a Cloud Dataprep job.
D) Use Cloud Dataflow to find null values in sample source data. Convert all nulls to using a custom script.

Google Professional Data Engineer Exam - Topic 1 Question 54 Discussion

Actual exam question for Google's Professional Data Engineer exam
Question #: 54
Topic #: 1
[All Professional Data Engineer Questions]

You are building a data pipeline on Google Cloud. You need to prepare data using a casual method for a

machine-learning process. You want to support a logistic regression model. You also need to monitor and

adjust for null values, which must remain real-valued and cannot be removed. What should you do?

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Suggested Answer: C

by Katina at Jun 29, 2022, 12:36 AM

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Frederica
9 months ago
Option C is interesting, but I prefer Dataflow for handling nulls.
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James
9 months ago
I agree with Ludivina, option B is definitely the way to go!
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Nan
10 months ago
Wait, can you really convert nulls to 'none' in a logistic regression model? Seems off.
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Ludivina
10 months ago
I think option B is the best choice! Converting nulls to 0 is a common practice.
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Fletcher
10 months ago
Option A sounds good, but converting nulls to 'none' might not work for real-valued data.
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Emmett
10 months ago
I vaguely remember that we shouldn't convert nulls to 'none' or 0 for logistic regression. I think we should keep them as real values, but I can't remember the exact method.
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Jeffrey
10 months ago
I feel like using Cloud Dataflow might be more appropriate for this scenario, but I'm uncertain about whether a custom script is necessary for handling nulls.
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Melda
10 months ago
I think we practiced a similar question where we used Cloud Dataprep to handle nulls, but I can't recall if converting them to 0 was the best option.
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Tanja
10 months ago
I remember we discussed how null values should be handled carefully, but I'm not sure if converting them to 'none' is the right approach for a logistic regression model.
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Glennis
10 months ago
Hmm, I'm not sure about this one. Bridging the vNIC sounds like the right approach, but I want to double-check that in my notes.
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Berry
11 months ago
Okay, let me see here. I believe the key is to run an automatic schedule request to generate the counts first, before entering any unscheduled entries.
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Graham
11 months ago
I think the key here is understanding the typical challenges faced by this specific customer group. Option A sounds like a safe bet, but I want to make sure I'm not missing something more specific to their situation. I'll read through the options again carefully.
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