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Google ADP Exam Syllabus Topics:

Google Associate Data Practitioner Sample Questions:

1. You are working on a project that requires analyzing daily social media dat a. You have 100 GB of JSON formatted data stored in Cloud Storage that keeps growing.
You need to transform and load this data into BigQuery for analysis. You want to follow the Google-recommended approach. What should you do?

A) Use Cloud Run functions to transform and load the data into BigQuery.
B) Use Cloud Data Fusion to transfer the data into BigQuery raw tables, and use SQL to transform it.
C) Manually download the data from Cloud Storage. Use a Python script to transform and upload the data into BigQuery.
D) Use Dataflow to transform the data and write the transformed data to BigQuery.

2. Your organization uses scheduled queries to perform transformations on data stored in BigQuery. You discover that one of your scheduled queries has failed. You need to troubleshoot the issue as quickly as possible. What should you do?

A) Navigate to the Scheduled queries page in the Google Cloud console. Select the failed job, and analyze the error details.
B) Request access from your admin to the BigQuery information_schema. Query the jobs view with the failed job ID, and analyze error details.
C) Navigate to the Logs Explorer page in Cloud Logging. Use filters to find the failed job, and analyze the error details.
D) Set up a log sink using the gcloud CLI to export BigQuery audit logs to BigQuery. Query those logs to identify the error associated with the failed job I

3. Your company uses Looker to generate and share reports with various stakeholders. You have a complex dashboard with several visualizations that needs to be delivered to specific stakeholders on a recurring basis, with customized filters applied for each recipient. You need an efficient and scalable solution to automate the delivery of this customized dashboard. You want to follow the Google- recommended approach. What should you do?

A) Create a separate LookML model for each stakeholder with predefined filters, and schedule the dashboards using the Looker Scheduler.
B) Embed the Looker dashboard in a custom web application, and use the application's scheduling features to send the report with personalized filters.
C) Create a script using the Looker Python SDK, and configure user attribute filter values. Generate a new scheduled plan for each stakeholder.
D) Use the Looker Scheduler with a user attribute filter on the dashboard, and send the dashboard with personalized filters to each stakeholder based on their attributes.

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

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

Solutions: