Google ADP : Associate Data Practitioner

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Google Associate Data Practitioner Sample Questions:

1. You have a BigQuery dataset containing sales dat
a. This data is actively queried for the first 6 months. After that, the data is not queried but needs to be retained for 3 years for compliance reasons. You need to implement a data management strategy that meets access and compliance requirements, while keeping cost and administrative overhead to a minimum. What should you do?

A) Set up a scheduled query to export the data to Cloud Storage after 6 months. Write a stored procedure to delete the data from BigQuery after 3 years.
B) Store all data in a single BigQuery table without partitioning or lifecycle policies.
C) Use BigQuery long-term storage for the entire dataset. Set up a Cloud Run function to delete the data from BigQuery after 3 years.
D) Partition a BigQuery table by month. After 6 months, export the data to Coldline storage. Implement a lifecycle policy to delete the data from Cloud Storage after 3 years.

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

3. 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.

4. 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) Create a Cloud Run function to load the data into BigQuery that is triggered when data arrives in Cloud Storage.
B) Create a Dataproc cluster to pull CSV files from Cloud Storage, process them using Spark, and write the results to BigQuery.
C) Create a Cloud Composer pipeline to load new files from Cloud Storage to BigQuery and schedule it to run every 10 minutes.
D) Use the bq command-line tool within a Cloud Shell instance to load the data into BigQuery.

5. Your company is migrating their batch transformation pipelines to Google Cloud. You need to choose a solution that supports programmatic transformations using only SQL. You also want the technology to support Git integration for version control of your pipelines. What should you do?

A) Use Cloud Composer operators.
B) Use Dataform workflows.
C) Use Dataflow pipelines.
D) Use Cloud Data Fusion pipelines.

Solutions: