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Google Associate Data Practitioner Sample Questions (Q21-Q26):
NEW QUESTION # 21
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 Dataform workflows.
- B. Use Cloud Data Fusion pipelines.
- C. Use Dataflow pipelines.
- D. Use Cloud Composer operators.
Answer: A
NEW QUESTION # 22
Your organization has several datasets in their data warehouse in BigQuery. Several analyst teams in different departments use the datasets to run queries. Your organization is concerned about the variability of their monthly BigQuery costs. You need to identify a solution that creates a fixed budget for costs associated with the queries run by each department. What should you do?
- A. Create a single reservation by using BigQuery editions. Assign all analysts to the reservation.
- B. Create a custom quota for each analyst in BigQuery.
- C. Assign each analyst to a separate project associated with their department. Create a single reservation for each department by using BigQuery editions. Create assignments for each project in the appropriate reservation.
- D. Assign each analyst to a separate project associated with their department. Create a single reservation by using BigQuery editions. Assign all projects to the reservation.
Answer: C
NEW QUESTION # 23
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 Dataflow job using the Dataflow job builder.
- B. Push event information to a Pub/Sub topic. Create a BigQuery subscription in Pub/Sub.
- 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 Cloud Storage, and create an external table in BigQuery. Create a BigQuery scheduled job that executes once each day to apply transformations.
Answer: A
NEW QUESTION # 24
Your data science team needs to collaboratively analyze a 25 TB BigQuery dataset to support the development of a machine learning model. You want to use Colab Enterprise notebooks while ensuring efficient data access and minimizing cost. What should you do?
- A. Export the BigQuery dataset to Google Drive. Load the dataset into the Colab Enterprise notebook using Pandas.
- B. Copy the BigQuery dataset to the local storage of the Colab Enterprise runtime, and analyze the data using Pandas.
- C. Create a Dataproc cluster connected to a Colab Enterprise notebook, and use Spark to process the data in BigQuery.
- D. Use BigQuery magic commands within a Colab Enterprise notebook to query and analyze the data.
Answer: D
NEW QUESTION # 25
Your company stores historical data in Cloud Storage. You need to ensure that all data is saved in a bucket for at least three years. What should you do?
- A. Change the bucket storage class to Archive.
- B. Enable Object Versioning.
- C. Set temporary object holds.
- D. Set a bucket retention policy.
Answer: D
NEW QUESTION # 26
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