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Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Data-Driven Decision Making	10-20%	- Assess data quality and completeness - Identify stakeholders and requirements - Translate business requirements into data solutions - Define success metrics
Data Visualization and Insights	20-30%	- Interpret and communicate findings - Choose appropriate visualization types - Build visualizations using Looker Studio - Present data insights to stakeholders - Create dashboards and reports
Data Processing and Analytics	20-30%	- Apply statistical methods for analysis - Use BigQuery and SQL for analytics - Query and analyze datasets - Build and maintain data pipelines - Aggregate and summarize data
Data Preparation and Exploration	20-30%	- Identify data quality issues - Ingest and acquire data - Transform and prepare data for analysis - Explore data through visualization and queries - Perform exploratory data analysis (EDA)

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Google Associate Data Practitioner Sample Questions (Q59-Q64):

NEW QUESTION # 59
Your organization has a petabyte of application logs stored as Parquet files in Cloud Storage. You need to quickly perform a one- time SQL-based analysis of the files and join them to data that already resides in BigQuery. What should you do?

A. Create external tables over the files in Cloud Storage, and perform SQL joins to tables in BigQuery to analyze the data.
B. Create a Dataproc cluster, and write a PySpark job to join the data from BigQuery to the files in Cloud Storage.
C. Launch a Cloud Data Fusion environment, use plugins to connect to BigQuery and Cloud Storage, and use the SQL join operation to analyze the data.
D. Use the bq load command to load the Parquet files into BigQuery, and perform SQL joins to analyze the data.

Answer: A

NEW QUESTION # 60
Your organization is building a new application on Google Cloud. Several data files will need to be stored in Cloud Storage. Your organization has approved only two specific cloud regions where these data files can reside. You need to determine a Cloud Storage bucket strategy that includes automated high availability.
What should you do?

A. Create a dual-region bucket, and upload the files to this bucket.
B. Create a multi-region bucket, and upload the files to this bucket.
C. Create a single-region bucket in each of the two regions, and use Storage Transfer Service to replicate the data across the buckets in both regions.
D. Create a single-region bucket in each of the two regions, and use the gcloud storage command to replicate the data across the buckets in both regions.

Answer: A

NEW QUESTION # 61
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.

Answer: C

NEW QUESTION # 62
You work for a home insurance company. You are frequently asked to create and save risk reports with charts for specific areas using a publicly available storm event dataset. You want to be able to quickly create and re- run risk reports when new data becomes available. What should you do?

A. Export the storm event dataset as a CSV file. Import the file to Google Sheets, and use cell data in the worksheets to create charts.
B. Reference and query the storm event dataset using SQL in a Colab Enterprise notebook. Display the table results and document with Markdown, and use Matplotlib to create charts.
C. Copy the storm event dataset into your BigQuery project. Use BigQuery Studio to query and visualize the data in Looker Studio.
D. Reference and query the storm event dataset using SQL in BigQuery Studio. Export the results to Google Sheets, and use cell data in the worksheets to create charts.

Answer: C

NEW QUESTION # 63
You recently inherited a task for managing Dataflow streaming pipelines in your organization and noticed that proper access had not been provisioned to you. You need to request a Google-provided IAM role so you can restart the pipelines. You need to follow the principle of least privilege. What should you do?

A. Request the Dataflow Developer role.
B. Request the Dataflow Admin role.
C. Request the Dataflow Worker role.
D. Request the Dataflow Viewer role.

Answer: A

NEW QUESTION # 64
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