Google Exam Professional-Data-Engineer Topic 4 Question 79 Discussion

Actual exam question for Google's Google Cloud Certified Professional Data Engineer exam

Question #: 79
Topic #: 4

[All Google Cloud Certified Professional Data Engineer Questions]

You want to create a machine learning model using BigQuery ML and create an endpoint foe hosting the model using Vertex Al. This will enable the processing of continuous streaming data in near-real time from multiple vendors. The data may contain invalid values. What should you do?

ACreate a new BigOuery dataset and use streaming inserts to land the data from multiple vendors. Configure your BigQuery ML model to use the 'ingestion' dataset as the training data.

BUse BigQuery streaming inserts to land the data from multiple vendors whore your BigQuery dataset ML model is deployed.

CCreate a Pub'Sub topic and send all vendor data to it Connect a Cloud Function to the topic to process the data and store it in BigQuery.

DCreate a Pub/Sub topic and send all vendor data to it Use Dataflow to process and sanitize the Pub/Sub data and stream it to BigQuery.

Show Suggested Answer

Suggested Answer: D

Dataflow provides a scalable and flexible way to process and clean the incoming data in real-time before loading it into BigQuery.

by Cristy at Mar 15, 2024, 07:12 AM

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Helene

8 days ago

You know, I was initially considering option C, but I think Dataflow might be a better choice here. It's designed for high-throughput, real-time data processing, which sounds like exactly what we need for this use case.

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Stefania

9 days ago

Hmm, I'm leaning towards option D. Using Pub/Sub to ingest the data and then leveraging Dataflow to process and sanitize it before streaming to BigQuery seems like a robust and scalable solution. Plus, Dataflow can handle the data transformation and cleaning, which is crucial given the potential for invalid values.

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Martha

10 days ago

Haha, for real! Trying to manually process all that vendor data would be a nightmare. Dataflow is definitely the way to go here. Plus, it integrates nicely with Pub/Sub and BigQuery, so the entire pipeline will be neatly tied together.

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Doyle

11 days ago

This question seems to be testing our understanding of real-time data processing and model deployment on Vertex AI. The key here is to identify the most efficient and scalable solution that can handle continuous streaming data from multiple vendors, while also addressing the issue of invalid values.

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