Professional-Data-Engineer Dumps - Google Professional Data Engineer Exam Practice Exam Questions

A.  

Create a Stackdriver Monitoring dashboard based on the BigQuery metric query/scanned_bytes

B.  

Create a Stackdriver Monitoring dashboard based on the BigQuery metric slots/allocated_for_project

C.  

Create a log export for each project, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric

D.  

Create an aggregated log export at the organization level, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric

A.  

Increase the share of the test sample in the train-test split.

B.  

Try to collect more data and increase the size of your dataset.

C.  

Try out regularization techniques (e.g., dropout of batch normalization) to avoid overfitting.

D.  

Increase the complexity of your model by, e.g., introducing an additional layer or increase sizing the size of vocabularies or n-grams used.

A.  

Import the data from Cloud Storage into BigQuery Create a new BigQuery table, and skip the rows with errors.

B.  

Create a Compute Engine instance and create a new copy of the data in Cloud Storage Skip the rows with errors

C.  

Create a Cloud Dataflow workflow that reads the data from Cloud Storage, checks for values outside the expected range, sets the value to an appropriate default, and writes the updated records to a new dataset in

Cloud Storage

D.  

Create a Cloud Dataflow workflow that reads the data from Cloud Storage, checks for values outside the expected range, sets the value to an appropriate default, and writes the updated records to the same dataset in Cloud Storage