Free Google Professional-Data-Engineer Exam Questions

You want to schedule a number of sequential load and transformation jobs Data files will be added to a Cloud

Storage bucket by an upstream process There is no fixed schedule for when the new data arrives Next, a

Dataproc job is triggered to perform some transformations and write the data to BigQuery. You then need to

run additional transformation jobs in BigQuery The transformation jobs are different for every table These

jobs might take hours to complete You need to determine the most efficient and maintainable workflow to

process hundreds of tables and provide the freshest data to your end users. What should you do?

You have a BigQuery table that ingests data directly from a Pub/Sub subscription. The ingested data is

encrypted with a Google-managed encryption key. You need to meet a new organization policy that requires

you to use keys from a centralized Cloud Key Management Service (Cloud KMS) project to encrypt data at

rest. What should you do?

You are running a Dataflow streaming pipeline, with Streaming Engine and Horizontal Autoscaling enabled.

You have set the maximum number of workers to 1000. The input of your pipeline is Pub/Sub messages with

notifications from Cloud Storage One of the pipeline transforms reads CSV files and emits an element for

every CSV line. The Job performance is low. the pipeline is using only 10 workers, and you notice that the

autoscaler is not spinning up additional workers. What should you do to improve performance?

You are designing a Dataflow pipeline for a batch processing job. You want to mitigate multiple zonal failures

at job submission time. What should you do?

MJTelco’s Google Cloud Dataflow pipeline is now ready to start receiving data from the 50,000 installations. You want to allow Cloud Dataflow to scale its compute power up as required. Which Cloud Dataflow pipeline configuration setting should you update?