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Answer: Use Cloud Dataprep to find null values in sample source data. Convert all nulls to 0 using a Cloud Dataprep job.
The correct answer is B: 'Use Cloud Dataprep to find null values in sample source data. Convert all nulls to 0 using a Cloud Dataprep job.' Cloud Dataprep is a data preparation service that provides an easy-to-use, visually interactive way to clean and transform data. Since the requirement specifies that the null values need to remain real-valued and cannot be removed, converting them to 0 is appropriate. Using Cloud Dataprep is the casual and straightforward method as compared to using custom scripts with Cloud Dataflow, which would require more expertise and is generally used for more complex processing.
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You are constructing a data pipeline on Google Cloud with the goal of preparing data for a machine-learning process. Your task is to support a logistic regression model. Additionally, you need to monitor and handle null values in the dataset, ensuring that these values remain real-valued and are not removed. What steps should you take to achieve this?
A
Use Cloud Dataprep to find null values in sample source data. Convert all nulls to 'none' using a Cloud Dataproc job.
B
Use Cloud Dataprep to find null values in sample source data. Convert all nulls to 0 using a Cloud Dataprep job.
C
Use Cloud Dataflow to find null values in sample source data. Convert all nulls to 'none' using a Cloud Dataprep job.
D
Use Cloud Dataflow to find null values in sample source data. Convert all nulls to 0 using a custom script.
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