Spring Sale Special Limited Time 70% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: buysanta

Exact2Pass Menu

Google Cloud Associate Data Practitioner (ADP Exam)

Last Update 15 hours ago Total Questions : 106

The Google Cloud Associate Data Practitioner (ADP Exam) content is now fully updated, with all current exam questions added 15 hours ago. Deciding to include Associate-Data-Practitioner practice exam questions in your study plan goes far beyond basic test preparation.

You'll find that our Associate-Data-Practitioner exam questions frequently feature detailed scenarios and practical problem-solving exercises that directly mirror industry challenges. Engaging with these Associate-Data-Practitioner sample sets allows you to effectively manage your time and pace yourself, giving you the ability to finish any Google Cloud Associate Data Practitioner (ADP Exam) practice test comfortably within the allotted time.

Question # 21

You want to process and load a daily sales CSV file stored in Cloud Storage into BigQuery for downstream reporting. You need to quickly build a scalable data pipeline that transforms the data while providing insights into data quality issues. What should you do?

A.

Create a batch pipeline in Cloud Data Fusion by using a Cloud Storage source and a BigQuery sink.

B.

Load the CSV file as a table in BigQuery, and use scheduled queries to run SQL transformation scripts.

C.

Load the CSV file as a table in BigQuery. Create a batch pipeline in Cloud Data Fusion by using a BigQuery source and sink.

D.

Create a batch pipeline in Dataflow by using the Cloud Storage CSV file to BigQuery batch template.

Question # 22

You are designing an application that will interact with several BigQuery datasets. You need to grant the application’s service account permissions that allow it to query and update tables within the datasets, and list all datasets in a project within your application. You want to follow the principle of least privilege. Which pre-defined IAM role(s) should you apply to the service account?

A.

roles/bigquery.jobUser and roles/bigquery.dataOwner

B.

roles/bigquery.connectionUser and roles/bigquery.dataViewer

C.

roles/bigquery.admin

D.

roles/bigquery.user and roles/bigquery.filteredDataViewer

Question # 23

You are developing a data ingestion pipeline to load small CSV files into BigQuery from Cloud Storage. You want to load these files upon arrival to minimize data latency. You want to accomplish this with minimal cost and maintenance. What should you do?

A.

Use the bq command-line tool within a Cloud Shell instance to load the data into BigQuery.

B.

Create a Cloud Composer pipeline to load new files from Cloud Storage to BigQuery and schedule it to run every 10 minutes.

C.

Create a Cloud Run function to load the data into BigQuery that is triggered when data arrives in Cloud Storage.

D.

Create a Dataproc cluster to pull CSV files from Cloud Storage, process them using Spark, and write the results to BigQuery.

Question # 24

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.

Set up a Cloud Scheduler job that invokes a weekly Cloud Run function to delete files older than seven days.

B.

Configure a Cloud Storage lifecycle rule that automatically deletes objects older than seven days.

C.

Develop a batch process using Dataflow that runs weekly and deletes files based on their age.

D.

Create a Cloud Run function that runs daily and deletes files older than seven days.

Question # 25

You manage a web application that stores data in a Cloud SQL database. You need to improve the read performance of the application by offloading read traffic from the primary database instance. You want to implement a solution that minimizes effort and cost. What should you do?

A.

Use Cloud CDN to cache frequently accessed data.

B.

Store frequently accessed data in a Memorystore instance.

C.

Migrate the database to a larger Cloud SQL instance.

D.

Enable automatic backups, and create a read replica of the Cloud SQL instance.

Question # 26

You created a customer support application that sends several forms of data to Google Cloud. Your application is sending:

1. Audio files from phone interactions with support agents that will be accessed during trainings.

2. CSV files of users’ personally identifiable information (Pll) that will be analyzed with SQL.

3. A large volume of small document files that will power other applications.

You need to select the appropriate tool for each data type given the required use case, while following Google-recommended practices. Which should you choose?

A.

1. Cloud Storage

2. CloudSQL for PostgreSQL

3. Bigtable

B.

1. Filestore

2. Cloud SQL for PostgreSQL

3. Datastore

C.

1. Cloud Storage

2. BigQuery

3. Firestore

D.

1. Filestore

2. Bigtable

3. BigQuery

Question # 27

You are using your own data to demonstrate the capabilities of BigQuery to your organization’s leadership team. You need to perform a one-time load of the files stored on your local machine into BigQuery using as little effort as possible. What should you do?

A.

Write and execute a Python script using the BigQuery Storage Write API library.

B.

Create a Dataproc cluster, copy the files to Cloud Storage, and write an Apache Spark job using the spark-bigquery-connector.

C.

Execute the bq load command on your local machine.

D.

Create a Dataflow job using the Apache Beam FileIO and BigQueryIO connectors with a local runner.

Question # 28

Your organization’s business analysts require near real-time access to streaming data. However, they are reporting that their dashboard queries are loading slowly. After investigating BigQuery query performance, you discover the slow dashboard queries perform several joins and aggregations.

You need to improve the dashboard loading time and ensure that the dashboard data is as up-to-date as possible. What should you do?

A.

Disable BiqQuery query result caching.

B.

Modify the schema to use parameterized data types.

C.

Create a scheduled query to calculate and store intermediate results.

D.

Create materialized views.

Question # 29

You are a Looker analyst. You need to add a new field to your Looker report that generates SQL that will run against your company's database. You do not have the Develop permission. What should you do?

A.

Create a new field in the LookML layer, refresh your report, and select your new field from the field picker.

B.

Create a calculated field using the Add a field option in Looker Studio, and add it to your report.

C.

Create a table calculation from the field picker in Looker, and add it to your report.

D.

Create a custom field from the field picker in Looker, and add it to your report.

Question # 30

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?

A.

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

B.

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

C.

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

D.

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

Go to page: