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Answer: Deploy Google Cloud Datalab to a virtual machine (VM) on Google Compute Engine.
The correct answer is D. Deploying Google Cloud Datalab to a virtual machine (VM) on Google Compute Engine is the best solution. Google Cloud Datalab provides a powerful interactive tool for data exploration, analysis, and machine learning, which is suitable for working with very large datasets. It offers the necessary computational power and is designed to handle the data processing tasks that the data scientist needs. Although Google Cloud Datalab has been deprecated and replaced by Vertex AI Workbench, the concept remains the same—deploying a robust and scalable environment to support data analysis tasks. The other options either do not offer sufficient computational power (A and B) or only cover a part of the required tasks (C).
Author: LeetQuiz Editorial Team
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Your company recently onboarded a new data scientist who aims to conduct complex analyses on extremely large datasets. These datasets are housed in Google Cloud Storage and a Cassandra cluster on Google Compute Engine. Her primary goal is to generate labeled datasets for machine learning initiatives and conduct some visualization tasks. She has indicated that her current laptop lacks the required processing power, causing significant delays in her work. To assist her in efficiently performing her tasks, what steps should you take?
A
Run a local version of Jupyter on the laptop.
B
Grant the user access to Google Cloud Shell.
C
Host a visualization tool on a VM on Google Compute Engine.
D
Deploy Google Cloud Datalab to a virtual machine (VM) on Google Compute Engine.
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