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Professional Data Engineer

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Topic 1 Question 65
You are building a data pipeline on Google Cloud. You need to prepare data using a casual method for a machine-learning process. You want to support a logistic regression model. You also need to monitor and adjust for null values, which must remain real-valued and cannot be removed. What should you do?
- Use Cloud Dataprep to find null values in sample source data. Convert all nulls to 'none' using a Cloud Dataproc job.
- Use Cloud Dataprep to find null values in sample source data. Convert all nulls to 0 using a Cloud Dataprep job.
- Use Cloud Dataflow to find null values in sample source data. Convert all nulls to 'none' using a Cloud Dataprep job.
- Use Cloud Dataflow to find null values in sample source data. Convert all nulls to 0 using a custom script.
ユーザの投票
コメント(17)
- real-valued can not be null N/A or empty, have to be “0”, so it has to be B.
  
  👍 37
  jvg6372020/03/16
- Should be B
  
  👍 16
  [Removed]2020/03/21
- Casual approach Dataprep ...and convert null value to numerical value to 0 ...answer B
  
  👍 5
  Tanmoyk2020/09/07
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