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Google ADP Exam Syllabus Topics:

Google Associate Data Practitioner Sample Questions:

Question 1

You are working with a large dataset of customer reviews stored in Cloud Storage. The dataset contains several inconsistencies, such as missing values, incorrect data types, and duplicate entries. You need toclean the data to ensure that it is accurate and consistent before using it for analysis. What should you do?

A. Use BigQuery to batch load the data into BigQuery. Use SQL for cleaning and analysis.
B. Use the PythonOperator in Cloud Composer to clean the data and load it into BigQuery. Use SQL for analysis.
C. Use Storage Transfer Service to move the data to a different Cloud Storage bucket. Use event triggers to invoke Cloud Run functions to load the data into BigQuery. Use SQL for analysis.
D. Use Cloud Run functions to clean the data and load it into BigQuery. Use SQL for analysis.

Question 2

Your company uses Looker to visualize and analyze sales dat
a. You need to create a dashboard that displays sales metrics, such as sales by region, product category, and time period. Each metric relies on its own set of attributes distributed across several tables. You need to provide users the ability to filter the data by specific sales representatives and view individual transactions. You want to follow the Google-recommended approach. What should you do?

A. Use Looker's custom visualization capabilities to create a single visualization that displays all the sales metrics with filtering and drill-down functionality.
B. Use BigQuery to create multiple materialized views, each focusing on a specific sales metric. Build the dashboard using these views.
C. Create a single Explore with all sales metrics. Build the dashboard using this Explore.
D. Create multiple Explores, each focusing on each sales metric. Link the Explores together in a dashboard using drill-down functionality.

Question 3

You need to create a weekly aggregated sales report based on a large volume of data. You want to use Python to design an efficient process for generating this report. What should you do?

A. Create a Dataflow directed acyclic graph (DAG) coded in Python. Use Cloud Scheduler to schedule the code to run once a week.
B. Create a Cloud Run function that uses NumPy. Use Cloud Scheduler to schedule the function to run once a week.
C. Create a Cloud Data Fusion and Wrangler flow. Schedule the flow to run once a week.
D. Create a Colab Enterprise notebook and use the bigframes.pandas library. Schedule the notebook to execute once a week.

Question 4

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

Question 5

Your company has an on-premises file server with 5 TB of data that needs to be migrated to Google Cloud.
The network operations team has mandated that you can only use up to 250 Mbps of the total available bandwidth for the migration. You need to perform an online migration to Cloud Storage. What should you do?

A. Use Storage Transfer Service to configure an agent-based transfer. Set the appropriate bandwidth limit for the agent pool.
B. Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the --no- clobber option.
C. Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the -- daisy-chain option.
D. Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google Cloud.

Solutions: