Online Access Free ADP Practice Test

You work for a healthcare company. You have a daily ETL pipeline that extracts patient data from a legacy system, transforms it, and loads it into BigQuery for analysis. The pipeline currently runs manually using a shell script. You want to automate this process and add monitoring to ensure pipeline observability and troubleshooting insights. You want one centralized solution, using open-source tooling, without rewriting the ETL code. What should you do?

• A.Use Cloud Scheduler to trigger a Dataproc job to execute the pipeline daily. Monitor the job's progress using the Dataproc job web interface and Cloud Monitoring.
• B.Configure Cloud Dataflow to implement the ETL pipeline, and use Cloud Scheduler to trigger the Dataflow pipeline daily. Monitor the pipelines execution using the Dataflow job monitoring interface and Cloud Monitoring.
• C.Create a Cloud Run function that runs the pipeline daily. Monitor the functions execution using Cloud Monitoring.
• D.Create a direct acyclic graph (DAG) in Cloud Composer to orchestrate a pipeline trigger daily. Monitor the pipeline's execution using the Apache Airflow web interface and Cloud Monitoring.

Your organization has a BigQuery dataset that contains sensitive employee information such as salaries and performance reviews. The payroll specialist in the HR department needs to have continuous access to aggregated performance data, but they do not need continuous access to other sensitive dat a. You need to grant the payroll specialist access to the performance data without granting them access to the entire dataset using the simplest and most secure approach. What should you do?

• A.Use authorized views to share query results with the payroll specialist.
• B.Create a table with the aggregated performance data. Use table-level permissions to grant access to the payroll specialist.
• C.Create a SQL query with the aggregated performance data. Export the results to an Avro file in a Cloud Storage bucket. Share the bucket with the payroll specialist.
• D.Create row-level and column-level permissions and policies on the table that contains performance data in the dataset. Provide the payroll specialist with the appropriate permission set.

You need to create a weekly aggregated sales report based on a large volume of data. You want to use Python to design an efficient process for generating this report. What should you do?

• A.Create a Cloud Run function that uses NumPy. Use Cloud Scheduler to schedule the function to run once a week.
• B.Create a Cloud Data Fusion and Wrangler flow. Schedule the flow to run once a week.
• C.Create a Dataflow directed acyclic graph (DAG) coded in Python. Use Cloud Scheduler to schedule the code to run once a week.
• D.Create a Colab Enterprise notebook and use the bigframes.pandas library. Schedule the notebook to execute once a week.

Your team is building several data pipelines that contain a collection of complex tasks and dependencies that you want to execute on a schedule, in a specific order. The tasks and dependencies consist of files in Cloud Storage, Apache Spark jobs, and data in BigQuery. You need to design a system that can schedule and automate these data processing tasks using a fully managed approach. What should you do?

• A.Use Cloud Scheduler to schedule the jobs to run.
• B.Create directed acyclic graphs (DAGS) in Cloud Composer. Use the appropriate operators to connect to Cloud Storage, Spark, and BigQuery.
• C.Use Cloud Tasks to schedule and run the jobs asynchronously.
• D.Create directed acyclic graphs (DAGS) in Apache Airflow deployed on Google Kubernetes Engine. Use the appropriate operators to connect to Cloud Storage, Spark, and BigQuery.

You manage a Cloud Storage bucket that stores temporary files created during data processing. These temporary files are only needed for seven days, after which they are no longer needed. To reduce storage costs and keep your bucket organized, you want to automatically delete these files once they are older than seven days. What should you do?

• A.Develop a batch process using Dataflow that runs weekly and deletes files based on their age.
• B.Configure a Cloud Storage lifecycle rule that automatically deletes objects older than seven days.
• C.Create a Cloud Run function that runs daily and deletes files older than seven days.
• D.Set up a Cloud Scheduler job that invokes a weekly Cloud Run function to delete files older than seven days.