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Answer: Provide the data science team access to Dataprep to prepare, validate, and explore the data within Cloud Storage.
The correct answer is D. Dataprep is a serverless, no-code data preparation tool that allows users to visually explore, cleanse, and prepare data for analysis. It is designed for business analysts, data scientists, and others who want to work with data without writing code. Dataprep can directly access and transform data in Cloud Storage, making it a suitable choice for a team that prefers a low-code, user-friendly solution.
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Your data science team has accumulated a variety of files stored in Google Cloud Storage. These files are intended for use in developing and refining machine learning models. However, the team currently lacks a method to explore, cleanse, and validate the data directly within the Cloud Storage environment. You are tasked with finding a low-code solution that will enable the data science team to efficiently perform data cleansing and exploration tasks within Cloud Storage. What should you do?
A
Provide the data science team access to Dataflow to create a pipeline to prepare and validate the raw data and load data into BigQuery for data exploration.
B
Create an external table in BigQuery and use SQL to transform the data as necessary. Provide the data science team access to the external tables to explore the raw data.
C
Load the data into BigQuery and use SQL to transform the data as necessary. Provide the data science team access to staging tables to explore the raw data.
D
Provide the data science team access to Dataprep to prepare, validate, and explore the data within Cloud Storage.
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