Expert Answers to Google Exam Associate-Data-Practitioner Questions

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Google Cloud Platform Google Cloud Associate Data Practitioner ( ADP Exam )

Google Cloud Associate Data Practitioner ( ADP Exam )

Last Update Jan 22, 2025
Total Questions : 72

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Questions 2

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?

Options:

Use Cloud Scheduler to schedule the jobs to run.

Use Cloud Tasks to schedule and run the jobs asynchronously.

Create directed acyclic graphs (DAGs) in Cloud Composer. Use the appropriate operators to connect to Cloud Storage, Spark, and BigQuery.

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.

Discussion 0

Questions 3

You are working with a large dataset of customer reviews stored in Cloud Storage. The dataset contains several inconsistencies, such as missing values, incorrect data types, and duplicate entries. You need to clean the data to ensure that it is accurate and consistent before using it for analysis. What should you do?

Options:

Use the PythonOperator in Cloud Composer to clean the data and load it into BigQuery. Use SQL for analysis.

Use BigQuery to batch load the data into BigQuery. Use SQL for cleaning and analysis.

Use Storage Transfer Service to move the data to a different Cloud Storage bucket. Use event triggers to invoke Cloud Run functions to load the data into BigQuery. Use SQL for analysis.

Use Cloud Run functions to clean the data and load it into BigQuery. Use SQL for analysis.

Discussion 0

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Questions 4

Your organization uses Dataflow pipelines to process real-time financial transactions. You discover that one of your Dataflow jobs has failed. You need to troubleshoot the issue as quickly as possible. What should you do?

Options:

Set up a Cloud Monitoring dashboard to track key Dataflow metrics, such as data throughput, error rates, and resource utilization.

Create a custom script to periodically poll the Dataflow API for job status updates, and send email alerts if any errors are identified.

Navigate to the Dataflow Jobs page in the Google Cloud console. Use the job logs and worker logs to identify the error.

Use the gcloud CLI tool to retrieve job metrics and logs, and analyze them for errors and performance bottlenecks.

Discussion 0

Questions 5

You have a Dataproc cluster that performs batch processing on data stored in Cloud Storage. You need to schedule a daily Spark job to generate a report that will be emailed to stakeholders. You need a fully-managed solution that is easy to implement and minimizes complexity. What should you do?

Options:

Use Cloud Composer to orchestrate the Spark job and email the report.

Use Dataproc workflow templates to define and schedule the Spark job, and to email the report.

Use Cloud Run functions to trigger the Spark job and email the report.

Use Cloud Scheduler to trigger the Spark job. and use Cloud Run functions to email the report.

Discussion 0

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