Google Associate Data Practitioner Sample Questions:

1. 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 Composer operators.
C) Use Cloud Data Fusion pipelines.
D) Use Dataflow pipelines.

2. Your organization needs to store historical customer order dat
a. The data will only be accessed once a month for analysis and must be readily available within a few seconds when it is accessed. You need to choose a storage class that minimizes storage costs while ensuring that the data can be retrieved quickly. What should you do?

A) Store the data in Cloud Storage using Coldline storage.
B) Store the data in Cloud Storage using Standard storage.
C) Store the data in Cloud Storage using Nearline storage.
D) Store the data in Cloud Storage using Archive storage.

3. 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) Enable Object Versioning.
B) Set a bucket retention policy.
C) Set temporary object holds.
D) Change the bucket storage class to Archive.

4. Your organization's website uses an on-premises MySQL as a backend database. You need to migrate the on-premises MySQL database to Google Cloud while maintaining MySQL features. You want to minimize administrative overhead and downtime. What should you do?

A) Use Database Migration Service to transfer the data to Cloud SQL for MySQL, and configure the on premises MySQL database as the source.
B) Install MySQL on a Compute Engine virtual machine. Export the database files using the mysqldump command. Upload the files to Cloud Storage, and import them into the MySQL instance on Compute Engine.
C) Use a Google-provided Dataflow template to replicate the MySQL database in BigQuery.
D) Export the database tables to CSV files, and upload the files to Cloud Storage. Convert the MySQL schema to a Spanner schema, create a JSON manifest file, and run a Google-provided Dataflow template to load the data into Spanner.

5. You have created a LookML model and dashboard that shows daily sales metrics for five regional managers to use. You want to ensure that the regional managers can only see sales metrics specific to their region. You need an easy-to-implement solution. What should you do?

A) Create five different Explores with thesql_always_filterExplore filter applied on theregion_namedimension. Set eachregion_namevalue to the corresponding region for each manager.
B) Add anaccess_filterExplore filter on theregion_namedimension by using thesales_regionuser attribute.
C) Create separate Looker dashboards for each regional manager. Set the default dashboard filter to the corresponding region for each manager.
D) Create asales_regionuser attribute, and assign each manager's region as the value of their user attribute.

Solutions: