Google ADP : Associate Data Practitioner

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Google Associate Data Practitioner Sample Questions:

1. Your company currently uses an on-premises network file system (NFS) and is migrating data to Google Cloud. You want to be able to control how much bandwidth is used by the data migration while capturing detailed reporting on the migration status. What should you do?

A) Use gcloud storage commands.
B) Use a Transfer Appliance.
C) Use Storage Transfer Service.
D) Use Cloud Storage FUSE.

2. Your organization has a petabyte of application logs stored as Parquet files in Cloud Storage. You need to quickly perform a one- time SQL-based analysis of the files and join them to data that already resides in BigQuery. What should you do?

A) Launch a Cloud Data Fusion environment, use plugins to connect to BigQuery and Cloud Storage, and use the SQL join operation to analyze the data.
B) Create a Dataproc cluster, and write a PySpark job to join the data from BigQuery to the files in Cloud Storage.
C) Use the bq load command to load the Parquet files into BigQuery, and perform SQL joins to analyze the data.
D) Create external tables over the files in Cloud Storage, and perform SQL joins to tables in BigQuery to analyze the data.

3. You have created a LookML model and dashboard that shows daily sales metrics for five regional managers to use. You want to ensure that the regional managers can only see sales metrics specific to their region. You need an easy-to-implement solution. What should you do?

A) Create five different Explores with thesql_always_filterExplore filter applied on theregion_namedimension. Set eachregion_namevalue to the corresponding region for each manager.
B) Create separate Looker dashboards for each regional manager. Set the default dashboard filter to the corresponding region for each manager.
C) Add anaccess_filterExplore filter on theregion_namedimension by using thesales_regionuser attribute.
D) Create asales_regionuser attribute, and assign each manager's region as the value of their user attribute.

4. Your organization has highly sensitive data that gets updated once a day and is stored across multiple datasets in BigQuery. You need to provide a new data analyst access to query specific data in BigQuery while preventing access to sensitive dat a. What should you do?

A) Grant the data analyst the BigQuery Job User IAM role in the Google Cloud project.
B) Create a new Google Cloud project, and copy the limited data into a BigQuery table. Grant the data analyst the BigQuery Data Owner IAM role in the new Google Cloud project.
C) Create a materialized view with the limited data in a new dataset. Grant the data analyst BigQuery Data Viewer IAM role in the dataset and the BigQuery Job User IAM role in the Google Cloud project.
D) Grant the data analyst the BigQuery Data Viewer IAM role in the Google Cloud project.

5. You need to create a data pipeline that streams event information from applications in multiple Google Cloud regions into BigQuery for near real-time analysis. The data requires transformation before loading. You want to create the pipeline using a visual interface. What should you do?

A) Push event information to a Pub/Sub topic. Create a BigQuery subscription in Pub/Sub.
B) Push event information to a Pub/Sub topic. Create a Dataflow job using the Dataflow job builder.
C) Push event information to Cloud Storage, and create an external table in BigQuery. Create a BigQuery scheduled job that executes once each day to apply transformations.
D) Push event information to a Pub/Sub topic. Create a Cloud Run function to subscribe to the Pub/Sub topic, apply transformations, and insert the data into BigQuery.

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