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

What are two methods that can be used to denormalize tables in BigQuery?

• A. 1) Use nested repeated fields; 2) Use a partitioned table
• B. 1) Use a partitioned table; 2) Join tables into one table
• C. 1) Split table into multiple tables; 2) Use a partitioned table
• D. 1) Join tables into one table; 2) Use nested repeated fields

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

You work for a shipping company that uses handheld scanners to read shipping labels. Your company has strict data privacy standards that require scanners to only transmit recipients' personally identifiable information (PII) to analytics systems, which violates user privacy rules. You want to quickly build a scalable solution using cloud-native managed services to prevent exposure of PII to the analytics systems. What should you do?

• A. Create an authorized view in BigQuery to restrict access to tables with sensitive data.
• B. Use Stackdriver logging to analyze the data passed through the total pipeline to identify transactions that may contain sensitive information.
• C. Install a third-party data validation tool on Compute Engine virtual machines to check the incoming data for sensitive information.
• D. Use the tagging and confidence levels to either pass or quarantine the data in a bucket for review.
• E. Build a Cloud Function that reads the topics and makes a call to the Cloud Data Loss Prevention AP

Which of the following job types are supported by Cloud Dataproc (select 3 answers)?

• A. YARN
• B. Spark
• C. Pig
• D. Hive