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Google ADP Exam Syllabus Topics:

Google Associate Data Practitioner Sample Questions:

1. 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 BigQuery table that uses the SUM() function and the DATE_DIFF() function.
B) Create a BigQuery table that uses the SUM() function and the _PARTITIONDATE filter.
C) Create a materialized view in BigQuery that uses the SUM() function and the DATE_SUB() function.
D) 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.

2. 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) Develop a batch process using Dataflow that runs weekly and deletes files based on their age.
B) Set up a Cloud Scheduler job that invokes a weekly Cloud Run function to delete files older than seven days.
C) Create a Cloud Run function that runs daily and deletes files older than seven days.
D) Configure a Cloud Storage lifecycle rule that automatically deletes objects older than seven days.

3. Your organization has a BigQuery dataset that contains sensitive employee information such as salaries and performance reviews. The payroll specialist in the HR department needs to have continuous access to aggregated performance data, but they do not need continuous access to other sensitive dat a. You need to grant the payroll specialist access to the performance data without granting them access to the entire dataset using the simplest and most secure approach. What should you do?

A) Use authorized views to share query results with the payroll specialist.
B) Create row-level and column-level permissions and policies on the table that contains performance data in the dataset. Provide the payroll specialist with the appropriate permission set.
C) Create a SQL query with the aggregated performance data. Export the results to an Avro file in a Cloud Storage bucket. Share the bucket with the payroll specialist.
D) Create a table with the aggregated performance data. Use table-level permissions to grant access to the payroll specialist.

4. 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 Cloud Storage, and create an external table in BigQuery. Create a BigQuery scheduled job that executes once each day to apply transformations.
C) 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.
D) Push event information to a Pub/Sub topic. Create a Dataflow job using the Dataflow job builder.

5. You used BigQuery ML to build a customer purchase propensity model six months ago. You want to compare the current serving data with the historical serving data to determine whether you need to retrain the model.
What should you do?

A) Compare the confusion matrix.
B) Evaluate the data skewness.
C) Compare the two different models.
D) Evaluate data drift.

Solutions: