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Google Data Engineer Sample Questions:

1. You have a data stored in BigQuery. The data in the BigQuery dataset must be highly available. You need to define a storage, backup, and recovery strategy of this data that minimizes cost. How should you configure the BigQuery table?

A) In the event of an emergency, use a point-in-time snapshot to recover the data.
B) In the event of an emergency, use a point-in-time snapshot to recover the data.
C) Create a scheduled query to make copies of the data to tables suffixed with the time of the backup
D) Set the BigQuery dataset to be regiona
E) Create a scheduled query to make copies of the data to tables suffixed with the time of the backu
F) In the event of an emergency, use the backup copy of the table.
G) Set the BigQuery dataset to be multi-regional
H) In the event of an emergency, use the backup copy of the table.
I) Set the BigQuery dataset to be multi-regional
J) Set the BigQuery dataset to be regiona

2. You are building a model to predict whether or not it will rain on a given day. You have thousands of input features and want to see if you can improve training speed by removing some features while having a minimum effect on model accuracy. What can you do?

A) Combine highly co-dependent features into one representative feature.
B) Eliminate features that are highly correlated to the output labels.
C) Remove the features that have null values for more than 50% of the training records.
D) Instead of feeding in each feature individually, average their values in batches of 3.

3. You need to deploy additional dependencies to all of a Cloud Dataproc cluster at startup using an existing initialization action. Company security policies require that Cloud Dataproc nodes do not have access to the Internet so public initialization actions cannot fetch resources. What should you do?

A) Use Resource Manager to add the service account used by the Cloud Dataproc cluster to the Network User role
B) Copy all dependencies to a Cloud Storage bucket within your VPC security perimeter
C) Deploy the Cloud SQL Proxy on the Cloud Dataproc master
D) Use an SSH tunnel to give the Cloud Dataproc cluster access to the Internet

4. You operate an IoT pipeline built around Apache Kafka that normally receives around 5000 messages per second. You want to use Google Cloud Platform to create an alert as soon as the moving average over 1 hour drops below 4000 messages per second. What should you do?

A) Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to BigQuer
B) Consume the stream of data in Cloud Dataflow using Kafka I
C) If that number falls below 4000, send an alert.
D) Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su
E) Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to Cloud Bigtabl
F) Consume the stream of data in Cloud Dataflow using Kafka I
G) Use Cloud Scheduler to run a script every hour that counts the number of rows created in Cloud Bigtable in the last hour
H) Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
I) Set a fixed time window of 1 hour.Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
J) Set a sliding time window of 1 hour every 5 minute
K) If that number falls below 4000, send an alert.
L) Use Cloud Scheduler to run a script every five minutes that counts the number of rows created in BigQuery in the last hour
M) Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su

5. Which Google Cloud Platform service is an alternative to Hadoop with Hive?

A) Cloud Bigtable
B) BigQuery
C) Cloud Datastore
D) Cloud Dataflow

Solutions: