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Google Certified Professional Data Engineer Exam Sample Questions (Q244-Q249):
NEW QUESTION # 244
MJTelco needs you to create a schema in Google Bigtable that will allow for the historical analysis of the last
2 years of records. Each record that comes in is sent every 15 minutes, and contains a unique identifier of the device and a data record. The most common query is for all the data for a given device for a given day. Which schema should you use?
- A. Rowkey: device_idColumn data: date, data_point
- B. Rowkey: dateColumn data: device_id, data_point
- C. Rowkey: data_pointColumn data: device_id, date
- D. Rowkey: date#device_idColumn data: data_point
- E. Rowkey: date#data_pointColumn data: device_id
Answer: C
NEW QUESTION # 245
You work for a large real estate firm and are preparing 6 TB of home sales data lo be used for machine learning You will use SOL to transform the data and use BigQuery ML lo create a machine learning model. You plan to use the model for predictions against a raw dataset that has not been transformed. How should you set up your workflow in order to prevent skew at prediction time?
- A. Preprocess all data using Dataflow. At prediction time, use BigOuery"s ML. EVALUATE clause without specifying any further transformations on the input data.
- B. When creating your model, use BigQuery's TRANSFORM clause to define preprocessing steps Before requesting predictions, use a saved query to transform your raw input data, and then use ML. EVALUATE
- C. When creating your model, use BigQuerys TRANSFORM clause to define preprocessing stops. At prediction time, use BigQuery"s ML. EVALUATE clause without specifying any transformations on the raw input data.
- D. Use a BigOuery to define your preprocessing logic. When creating your model, use the view as your model training data. At prediction lime, use BigQuery's ML EVALUATE clause without specifying any transformations on the raw input data.
Answer: C
Explanation:
https://cloud.google.com/bigquery-ml/docs/bigqueryml-transform Using the TRANSFORM clause, you can specify all preprocessing during model creation. The preprocessing is automatically applied during the prediction and evaluation phases of machine learning
NEW QUESTION # 246
You have some data, which is shown in the graphic below. The two dimensions are X and Y, and the shade of each dot represents what class it is. You want to classify this data accurately using a linear algorithm.
To do this you need to add a synthetic feature. What should the value of that feature be?
- A. cos(X)
- B. X
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