Online Access Free Associate-Data-Practitioner Practice Test

Your organization sends IoT event data to a Pub/Sub topic. Subscriber applications read and perform transformations on the messages before storing them in the data warehouse. During particularly busy times when more data is being written to the topic, you notice that the subscriber applications are not acknowledging messages within the deadline. You need to modify your pipeline to handle these activity spikes and continue to process the messages. What should you do?

• A.Retry messages until they are acknowledged.
  B Implement flow control on the subscribers
• B.Seek back to the last acknowledged message.
• C.Forward unacknowledged messages to a dead-letter topic.

You work for an ecommerce company that has a BigQuery dataset that contains customer purchase history, demographics, and website interactions. You need to build a machine learning (ML) model to predict which customers are most likely to make a purchase in the next month. You have limited engineering resources and need to minimize the ML expertise required for the solution. What should you do?

• A.Export the data to Cloud Storage, and use AutoML Tables to build a classification model for purchase prediction.
• B.Use BigQuery ML to create a logistic regression model for purchase prediction.
• C.Use Vertex AI Workbench to develop a custom model for purchase prediction.
• D.Use Colab Enterprise to develop a custom model for purchase prediction.

Your team wants to create a monthly report to analyze inventory data that is updated daily. You need to aggregate the inventory counts by using only the most recent month of data, and save the results to be used in a Looker Studio dashboard. What should you do?

• A.Create a saved query in the BigQuery console that uses the SUM( ) function and the DATE_SUB( ) function. Re-run the saved query every month, and save the results to a BigQuery table.
• B.Create a BigQuery table that uses the SUM( ) function and the DATE_DIFF( ) function.
• C.Create a materialized view in BigQuery that uses the SUM( ) function and the DATE_SUB( ) function.
• D.Create a BigQuery table that uses the SUM( ) function and the _PARTITIONDATE filter.

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 data. 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.

You are a data analyst working with sensitive customer data in BigQuery. You need to ensure that only authorized personnel within your organization can query this data, while following the principle of least privilege. What should you do?

• A.Enable access control by using IAM roles.
• B.Encrypt the data by using customer-managed encryption keys (CMEK).
• C.Export the data to Cloud Storage, and use signed URLs to authorize access.
• D.Update dataset privileges by using the SQL GRANT statement.