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Google ADP Exam Syllabus Topics:

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

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Google Associate Data Practitioner Sample Questions (Q14-Q19):

NEW QUESTION # 14
Your company is migrating their batch transformation pipelines to Google Cloud. You need to choose a solution that supports programmatic transformations using only SQL. You also want the technology to support Git integration for version control of your pipelines. What should you do?

A. Use Cloud Data Fusion pipelines.
B. Use Cloud Composer operators.
C. Use Dataflow pipelines.
D. Use Dataform workflows.

Answer: D

NEW QUESTION # 15
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 to BigQuery subscription, write results directly to BigQuery, and schedule a transformation query to run every five minutes.
B. Use the "Pub/Sub to BigQuery" Dataflow template with a UDF, and write the results to BigQuery.
C. Use a Pub/Sub push subscription, write a Cloud Run service that accepts the messages, performs the transformations, and writes the results to BigQuery.
D. 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.

Answer: B

NEW QUESTION # 16
Your company currently uses an on-premises network file system (NFS) and is migrating data to Google Cloud. You want to be able to control how much bandwidth is used by the data migration while capturing detailed reporting on the migration status. What should you do?

A. Use Storage Transfer Service.
B. Use gcloud storage commands.
C. Use a Transfer Appliance.
D. Use Cloud Storage FUSE.

Answer: A

NEW QUESTION # 17
You need to design a data pipeline to process large volumes of raw server log data stored in Cloud Storage.
The data needs to be cleaned, transformed, and aggregated before being loaded into BigQuery for analysis.
The transformation involves complex data manipulation using Spark scripts that your team developed. You need to implement a solution that leverages your team's existing skillset, processes data at scale, and minimizes cost. What should you do?

A. Use Dataform to define the transformations in SQLX.
B. Use Cloud Data Fusion to visually design and manage the pipeline.
C. Use Dataproc to run the transformations on a cluster.
D. Use Dataflow with a custom template for the transformation logic.

Answer: C

NEW QUESTION # 18
Your organization has several datasets in their data warehouse in BigQuery. Several analyst teams in different departments use the datasets to run queries. Your organization is concerned about the variability of their monthly BigQuery costs. You need to identify a solution that creates a fixed budget for costs associated with the queries run by each department. What should you do?

A. Assign each analyst to a separate project associated with their department. Create a single reservation by using BigQuery editions. Assign all projects to the reservation.
B. Create a single reservation by using BigQuery editions. Assign all analysts to the reservation.
C. Create a custom quota for each analyst in BigQuery.
D. Assign each analyst to a separate project associated with their department. Create a single reservation for each department by using BigQuery editions. Create assignments for each project in the appropriate reservation.

Answer: D

NEW QUESTION # 19
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