Exam Professional Data Engineer All Questions

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Exam Professional Data Engineer topic 1 question 96 discussion

Actual exam question from Google's Professional Data Engineer

Question #: 96
Topic #: 1

[All Professional Data Engineer Questions]

You want to analyze hundreds of thousands of social media posts daily at the lowest cost and with the fewest steps.
You have the following requirements:
✑ You will batch-load the posts once per day and run them through the Cloud Natural Language API.
✑ You will extract topics and sentiment from the posts.
✑ You must store the raw posts for archiving and reprocessing.
✑ You will create dashboards to be shared with people both inside and outside your organization.
You need to store both the data extracted from the API to perform analysis as well as the raw social media posts for historical archiving. What should you do?

A. Store the social media posts and the data extracted from the API in BigQuery.
B. Store the social media posts and the data extracted from the API in Cloud SQL.
C. Store the raw social media posts in Cloud Storage, and write the data extracted from the API into BigQuery.
D. Feed to social media posts into the API directly from the source, and write the extracted data from the API into BigQuery.

Show Suggested Answer

Suggested Answer: C 🗳️

by rickywck at March 17, 2020, 9:51 a.m.

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Highly Voted 3 years, 8 months ago

Answer: C Description: Social media posts can images/videos which cannot be stored in bigquery

upvoted 46 times

Shawvin

2 years, 1 month ago

Yes, the raw data needs to be archived too

upvoted 1 times

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Devx198912233

3 years, 5 months ago

but the posts are fed into cloud natural language api. which means we have to consider the posts to be text only

upvoted 4 times

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asksathvik

2 years, 3 months ago

Also to run batch queries data needs to be in Cloud Storage, so why not just store it there?

upvoted 1 times

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psu

Highly Voted 3 years, 8 months ago

Answer should be C, becose they ask you to save a copy of the raw posts for archival, which may not be possible if you directly feed the posts to the API.

upvoted 17 times

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itz_me_sudhir

Most Recent 9 months, 2 weeks ago

can any one help me with the rest of question from 101 to 209 as i dont have a contributor access

upvoted 2 times

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zellck

1 year ago

Selected Answer: C

C is the answer.

upvoted 2 times

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sedado77

1 year, 2 months ago

Selected Answer: C

I got this question on sept 2022. Answer is C

upvoted 5 times

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Erso

1 year, 3 months ago

Selected Answer: C

C is the correct one

upvoted 1 times

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medeis_jar

1 year, 11 months ago

Selected Answer: C

Only C make sense.

upvoted 2 times

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MaxNRG

1 year, 11 months ago

Selected Answer: C

You must store the raw posts for archiving and reprocessing, Store the raw social media posts in Cloud Storage. B is expensive D is not valid since you have to store the raw posts for archiving Between A and C I’s say C, since we’re going to make dashboards and Data Studio will connect well with big query. and besides A would probably be more expensive.

upvoted 3 times

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BigQuery

2 years ago

SAY MY NAME!

upvoted 4 times

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StefanoG

2 years ago

Selected Answer: C

Analysis BQ Storage GCS

upvoted 2 times

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fire558787

2 years, 4 months ago

I believe the API accesses data only from GCS Buckets not BigQuery (but I'm not entirely sure)

upvoted 1 times

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sumanshu

2 years, 5 months ago

Vote for C

upvoted 2 times

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DPonly

2 years, 11 months ago

Answer should be C because we need to consider storage archival

upvoted 2 times

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arghya13

3 years, 1 month ago

I'll go with option C

upvoted 2 times

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Alasmindas

3 years, 1 month ago

I will go with Option C, because of the following reasons:- a) Social media posts are "raw" - which means - it can be of any format (blob/object storage) is preferred. b) The output from the application (assuming the application is Cloud NLP) is to be future stored for archival purpose - and hence again Google Cloud storage is the best option - so option C Option A &C - Incorrect, although Option D fulfils the requirement of "fewest step" but storing data in big query for archival purpose is not a google recommended approach Option B : Cloud SQL rules out as it does not solve either for archival storage or for analytics purpose.

upvoted 3 times

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singhkrishna

3 years, 2 months ago

cost of long term storing is almost same in GCS and BQ, so answer D makes sense from that angle..

upvoted 1 times

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Tanmoyk

3 years, 3 months ago

The job is supposed to run in batch process once in a day , so there is no requirement of stream data. The best economical and less complex steps is answer C

upvoted 2 times

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