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Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data-Driven Decision Making	10-20%	- Identify stakeholders and requirements - Assess data quality and completeness - Translate business requirements into data solutions - Define success metrics
Topic 2: Data Preparation and Exploration	20-30%	- Identify data quality issues - Transform and prepare data for analysis - Explore data through visualization and queries - Perform exploratory data analysis (EDA) - Ingest and acquire data
Topic 3: Data Processing and Analytics	20-30%	- Apply statistical methods for analysis - Use BigQuery and SQL for analytics - Build and maintain data pipelines - Query and analyze datasets - Aggregate and summarize data
Topic 4: Data Visualization and Insights	20-30%	- Build visualizations using Looker Studio - Present data insights to stakeholders - Create dashboards and reports - Interpret and communicate findings - Choose appropriate visualization types

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Google Associate Data Practitioner Sample Questions (Q32-Q37):

NEW QUESTION # 32
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 materialized view that performs a union across all of the regional sales tables. Use the rank() window function to query the new materialized view.
B. 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.
C. 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.
D. 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.

Answer: A

NEW QUESTION # 33
Your organization uses Dataflow pipelines to process real-time financial transactions. You discover that one of your Dataflow jobs has failed. You need to troubleshoot the issue as quickly as possible. What should you do?

A. Use the gcloud CLI tool to retrieve job metrics and logs, and analyze them for errors and performance bottlenecks.
B. Create a custom script to periodically poll the Dataflow API for job status updates, and send email alerts if any errors are identified.
C. Set up a Cloud Monitoring dashboard to track key Dataflow metrics, such as data throughput, error rates, and resource utilization.
D. Navigate to the Dataflow Jobs page in the Google Cloud console. Use the job logs and worker logs to identify the error.

Answer: D

NEW QUESTION # 34
Your company's customer support audio files are stored in a Cloud Storage bucket. You plan to analyze the audio files' metadata and file content within BigQuery to create inference by using BigQuery ML. You need to create a corresponding table in BigQuery that represents the bucket containing the audio files. What should you do?

A. Create an object table.
B. Create a temporary table.
C. Create a native table.
D. Create an external table.

Answer: A

NEW QUESTION # 35
Your company is building a near real-time streaming pipeline to process JSON telemetry data from small appliances. You need to process messages arriving at a Pub/Sub topic, capitalize letters in the serial number field, and write results to BigQuery. You want to use a managed service and write a minimal amount of code for underlying transformations. What should you do?

A. Use a Pub/Sub push subscription, write a Cloud Run service that accepts the messages, performs the transformations, and writes the results to BigQuery.
B. Use a Pub/Sub to Cloud Storage subscription, write a Cloud Run service that is triggered when objects arrive in the bucket, performs the transformations, and writes the results to BigQuery.
C. Use the "Pub/Sub to BigQuery" Dataflow template with a UDF, and write the results to BigQuery.
D. Use a Pub/Sub to BigQuery subscription, write results directly to BigQuery, and schedule a transformation query to run every five minutes.

Answer: C

NEW QUESTION # 36
Your organization has highly sensitive data that gets updated once a day and is stored across multiple datasets in BigQuery. You need to provide a new data analyst access to query specific data in BigQuery while preventing access to sensitive dat a. What should you do?

A. Create a materialized view with the limited data in a new dataset. Grant the data analyst BigQuery Data Viewer IAM role in the dataset and the BigQuery Job User IAM role in the Google Cloud project.
B. Grant the data analyst the BigQuery Data Viewer IAM role in the Google Cloud project.
C. Create a new Google Cloud project, and copy the limited data into a BigQuery table. Grant the data analyst the BigQuery Data Owner IAM role in the new Google Cloud project.
D. Grant the data analyst the BigQuery Job User IAM role in the Google Cloud project.

Answer: A

NEW QUESTION # 37
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