Free Professional Data Engineer Exam Braindumps
Google Cloud Data Engineer Professional Questions 186–190 (page: 39)

Updated On: 10-Feb-2026

You are creating a new pipeline in Google Cloud to stream IoT data from Cloud Pub/Sub through Cloud Dataflow to BigQuery.
While previewing the data, you notice that roughly 2% of the data appears to be corrupt. You need to modify the Cloud Dataflow pipeline to filter out this corrupt dat

  1. What should you do?
  2. Add a SideInput that returns a Boolean if the element is corrupt.
  3. Add a ParDo transform in Cloud Dataflow to discard corrupt elements.
  4. Add a Partition transform in Cloud Dataflow to separate valid data from corrupt data.
  5. Add a GroupByKey transform in Cloud Dataflow to group all of the valid data together and discard the rest.

Answer(s): B



You have historical data covering the last three years in BigQuery and a data pipeline that delivers new data to BigQuery daily. You have noticed that when the Data Science team runs a query filtered on a date column and limited to 30­90 days of data, the query scans the entire table. You also noticed that your bill is increasing more quickly than you expected. You want to resolve the issue as cost-effectively as possible while maintaining the ability to conduct SQL queries.
What should you do?

  1. Re-create the tables using DDL. Partition the tables by a column containing a TIMESTAMP or DATE Type.
  2. Recommend that the Data Science team export the table to a CSV file on Cloud Storage and use Cloud Datalab to explore the data by reading the files directly.
  3. Modify your pipeline to maintain the last 30­90 days of data in one table and the longer history in a different table to minimize full table scans over the entire history.
  4. Write an Apache Beam pipeline that creates a BigQuery table per day. Recommend that the Data
    Science team use wildcards on the table name suffixes to select the data they need.

Answer(s): C



You operate a logistics company, and you want to improve event delivery reliability for vehicle-based sensors. You operate small data centers around the world to capture these events, but leased lines that provide connectivity from your event collection infrastructure to your event processing infrastructure are unreliable, with unpredictable latency. You want to address this issue in the most cost-effective way.
What should you do?

  1. Deploy small Kafka clusters in your data centers to buffer events.
  2. Have the data acquisition devices publish data to Cloud Pub/Sub.
  3. Establish a Cloud Interconnect between all remote data centers and Google.
  4. Write a Cloud Dataflow pipeline that aggregates all data in session windows.

Answer(s): B



You are a retailer that wants to integrate your online sales capabilities with different in-home assistants, such as Google Home. You need to interpret customer voice commands and issue an order to the backend systems.
Which solutions should you choose?

  1. Cloud Speech-to-Text API
  2. Cloud Natural Language API
  3. Dialogflow Enterprise Edition
  4. Cloud AutoML Natural Language

Answer(s): C



Your company has a hybrid cloud initiative. You have a complex data pipeline that moves data between cloud provider services and leverages services from each of the cloud providers.
Which cloud-native service should you use to orchestrate the entire pipeline?

  1. Cloud Dataflow
  2. Cloud Composer
  3. Cloud Dataprep
  4. Cloud Dataproc

Answer(s): D



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