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Google Associate Data Practitioner Exam - Topic 2 Question 30 Discussion

You are working on a project that requires analyzing daily social media data. You have 100 GB of JSON formatted data stored in Cloud Storage that keeps growing.You need to transform and load this data into BigQuery for analysis. You want to follow the Google-recommended approach. What should you do?
C) Use Dataflow to transform the data and write the transformed data to BigQuery.
A) Manually download the data from Cloud Storage. Use a Python script to transform and upload the data into BigQuery.
B) Use Cloud Run functions to transform and load the data into BigQuery.
D) Use Cloud Data Fusion to transfer the data into BigQuery raw tables, and use SQL to transform it.

Google Associate Data Practitioner Exam - Topic 2 Question 30 Discussion

Actual exam question for Google's Associate Data Practitioner exam
Question #: 30
Topic #: 2
[All Associate Data Practitioner Questions]

You are working on a project that requires analyzing daily social media dat

a. You have 100 GB of JSON formatted data stored in Cloud Storage that keeps growing.

You need to transform and load this data into BigQuery for analysis. You want to follow the Google-recommended approach. What should you do?

Show Suggested Answer Hide Answer
Suggested Answer: C

Comprehensive and Detailed in Depth

Why C is correct:Dataflow is a fully managed service for transforming and enriching data in both batch and streaming modes.

Dataflow is googles recomended way to transform large datasets.

It is designed for parallel processing, making it suitable for large datasets.

Why other options are incorrect:A: Manual downloading and scripting is not scalable or efficient.

B: Cloud Run functions are for stateless applications, not large data transformations.

D: While Cloud Data fusion could work, Dataflow is more optimized for large scale data transformation.


Dataflow: https://cloud.google.com/dataflow/docs

Query successful

by Blythe at Aug 15, 2026, 11:22 PM

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Vallie
3 days ago
Not sure about D, seems like extra steps for a simple task.
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Annelle
8 days ago
Totally agree with C! Google recommends it for a reason.
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Sharen
14 days ago
Wait, can Dataflow really handle that much data?
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Rasheeda
19 days ago
I think B could work too, but Dataflow is more efficient.
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Elbert
24 days ago
C is the way to go! Dataflow is perfect for this.
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Tamekia
29 days ago
I recall that using SQL for transformations in Cloud Data Fusion can be useful, but I think for large JSON data, Dataflow might be more scalable.
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Selma
1 month ago
I’m a bit confused about the options. I know Cloud Run is great for serverless functions, but I’m not sure it’s the best for this kind of data transformation.
upvoted 0 times
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Glenn
1 month ago
I practiced a similar question where we had to choose between Dataflow and Cloud Data Fusion. I feel like Dataflow might be the right answer for transforming data efficiently.
upvoted 0 times
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Vinnie
1 month ago
I think I remember that Dataflow is often recommended for handling large datasets like this, but I'm not completely sure if it's the best choice here.
upvoted 0 times
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