Online Access Free Associate-Data-Practitioner Practice Test

Your organization's ecommerce website collects user activity logs using a Pub/Sub topic. Your organization's leadership team wants a dashboard that contains aggregated user engagement metrics. You need to create a solution that transforms the user activity logs into aggregated metrics, while ensuring that the raw data can be easily queried. What should you do?

• A.Create a BigQuery subscription to the Pub/Sub topic, and load the activity logs into the table. Create a materialized view in BigQuery using SQL to transform the data for reporting
• B.Create a Cloud Storage subscription to the Pub/Sub topic. Load the activity logs into a bucket using the Avro file format. Use Dataflow to transform the data, and load it into a BigQuery table for reporting.
• C.Create an event-driven Cloud Run function to trigger a data transformation pipeline to run. Load the transformed activity logs into a BigQuery table for reporting.
• D.Create a Dataflow subscription to the Pub/Sub topic, and transform the activity logs. Load the transformed data into a BigQuery table for reporting.

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

You manage a large amount of data in Cloud Storage, including raw data, processed data, and backups. Your organization is subject to strict compliance regulations that mandate data immutability for specific data types.
You want to use an efficient process to reduce storage costs while ensuring that your storage strategy meets retention requirements. What should you do?

• A.Create a Cloud Run function to periodically check object metadata, and move objects to the appropriate storage class based on age and access patterns. Use object holds to enforce immutability for specific objects.
• B.Configure lifecycle management rules to transition objects to appropriate storage classes based on access patterns. Set up Object Versioning for all objects to meet immutability requirements.
• C.Move objects to different storage classes based on their age and access patterns. Use Cloud Key Management Service (Cloud KMS) to encrypt specific objects with customer-managed encryption keys (CMEK) to meet immutability requirements.
• D.Use object holds to enforce immutability for specific objects, and configure lifecycle management rules to transition objects to appropriate storage classes based on age and access patterns.

You are designing a pipeline to process data files that arrive in Cloud Storage by 3:00 am each day. Data processing is performed in stages, where the output of one stage becomes the input of the next. Each stage takes a long time to run. Occasionally a stage fails, and you have to address the problem. You need to ensure that the final output is generated as quickly as possible. What should you do?

• A.Design the processing as a directed acyclic graph (DAG) in Cloud Composer. Clear the state of the failed task after correcting any stage output data errors.
• B.Design a Spark program that runs under Dataproc. Code the program to wait for user input when an error is detected. Rerun the last action after correcting any stage output data errors.
• C.Design the pipeline as a set of PTransforms in Dataflow. Restart the pipeline after correcting any stage output data errors.
• D.Design the workflow as a Cloud Workflow instance. Code the workflow to jump to a given stage based on an input parameter. Rerun the workflow after correcting any stage output data errors.

Your company has an on-premises file server with 5 TB of data that needs to be migrated to Google Cloud.
The network operations team has mandated that you can only use up to 250 Mbps of the total available bandwidth for the migration. You need to perform an online migration to Cloud Storage. What should you do?

• A.Use the gcloud storage cp command to copy all files from on-premises to Cloud Storage using the -- daisy-chain option.
• B.Use Storage Transfer Service to configure an agent-based transfer. Set the appropriate bandwidth limit for the agent pool.
• C.Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google Cloud.
• D.Use the gcloud storage cp command to copy all files from on-premises to Cloud Storage using the --no- clobber option.