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Google ADP Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Management | 25% | - Data governance and security
|
| Data Preparation and Ingestion | 30% | - Data ingestion into Google Cloud services
|
| Data Analysis and Presentation | 27% | - Querying and analyzing data
|
| Data Pipeline Orchestration | 18% | - Pipeline design and automation
|
Google Associate Data Practitioner Sample Questions:
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 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.
- B. Create a BigQuery table that uses the SUM() function and the DATE_DIFF() function.
- C. Create a materialized view in BigQuery that uses the SUM() function and the DATE_SUB() function.
- D. Create a BigQuery table that uses the SUM() function and the _PARTITIONDATE filter.
Correct Answer: C 🗳️
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 Cloud Run function that uses NumPy. Use Cloud Scheduler to schedule the function to run once a week.
- B. Create a Colab Enterprise notebook and use the bigframes.pandas library. Schedule the notebook to execute once a week.
- C. Create a Cloud Data Fusion and Wrangler flow. Schedule the flow to run once a week.
- D. Create a Dataflow directed acyclic graph (DAG) coded in Python. Use Cloud Scheduler to schedule the code to run once a week.
Correct Answer: D 🗳️
Your organization is conducting analysis on regional sales metrics. Data from each regional sales team is stored as separate tables in BigQuery and updated monthly. You need to create a solution that identifies the top three regions with the highest monthly sales for the next three months. You want the solution to automatically provide up-to-date results. What should you do?
- A. Create a BigQuery table that performs a union across all of the regional sales tables. Use the row_number() window function to query the new table.
- B. Create a BigQuery table that performs a cross join across all of the regional sales tables. Use the rank() window function to query the new table.
- C. Create a BigQuery materialized view that performs a union across all of the regional sales tables. Use the rank() window function to query the new materialized view.
- D. Create a BigQuery materialized view that performs a cross join across all of the regional sales tables. Use the row_number() window function to query the new materialized view.
Correct Answer: C 🗳️
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 script using the Looker Python SDK, and configure user attribute filter values. Generate a new scheduled plan for each stakeholder.
- 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. Embed the Looker dashboard in a custom web application, and use the application's scheduling features to send the report with personalized filters.
- D. Create a separate LookML model for each stakeholder with predefined filters, and schedule the dashboards using the Looker Scheduler.
Correct Answer: B 🗳️
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.
Correct Answer: A 🗳️
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