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Google ADP Exam Syllabus Topics:

Google Associate Data Practitioner Sample Questions:

1. Your organization has decided to move their on-premises Apache Spark-based workload to Google Cloud.
You want to be able to manage the code without needing to provision and manage your own cluster. What should you do?

A) Migrate the Spark jobs to Dataproc Serverless.
B) Migrate the Spark jobs to Dataproc on Compute Engine.
C) Configure a Google Kubernetes Engine cluster with Spark operators, and deploy the Spark jobs.
D) Migrate the Spark jobs to Dataproc on Google Kubernetes Engine.

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

3. 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 a Pub/Sub topic. Create a Dataflow job using the Dataflow job builder.
C) 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.
D) 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.

4. 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.

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

Solutions: