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Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Data Analysis and Presentation	27%	- Data visualization 1. Looker / Looker Studio reporting - Querying and analyzing data 1. BigQuery SQL usage 2. Data aggregation and transformation
Data Management	25%	- Storage and data organization 1. BigQuery datasets and tables management 2. Cloud Storage lifecycle policies - Data governance and security 1. IAM and access control 2. Data lifecycle management
Data Pipeline Orchestration	18%	- Pipeline design and automation 1. Dataflow pipelines 2. Workflow orchestration concepts (e.g., Cloud Composer)
Data Preparation and Ingestion	30%	- Data ingestion into Google Cloud services 1. Streaming ingestion with Pub/Sub concepts 2. Cloud Storage ingestion patterns

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Google Associate Data Practitioner Sample Questions (Q17-Q22):

NEW QUESTION # 17
You need to create a data pipeline that streams event information from applications in multiple Google Cloud regions into BigQuery for near real-time analysis. The data requires transformation before loading. You want to create the pipeline using a visual interface. What should you do?

A. Push event information to a Pub/Sub topic. Create a Cloud Run function to subscribe to the Pub/Sub topic, apply transformations, and insert the data into BigQuery.
B. Push event information to a Pub/Sub topic. Create a Dataflow job using the Dataflow job builder.
C. Push event information to a Pub/Sub topic. Create a BigQuery subscription in Pub/Sub.
D. Push event information to Cloud Storage, and create an external table in BigQuery. Create a BigQuery scheduled job that executes once each day to apply transformations.

Answer: B

NEW QUESTION # 18
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 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.
B. Use a Pub/Sub push subscription, write a Cloud Run service that accepts the messages, performs the transformations, and writes the results to BigQuery.
C. Use a Pub/Sub to BigQuery subscription, write results directly to BigQuery, and schedule a transformation query to run every five minutes.
D. Use the "Pub/Sub to BigQuery" Dataflow template with a UDF, and write the results to BigQuery.

Answer: D

NEW QUESTION # 19
Your organization has decided to move their on-premises Apache Spark-based workload to Google Cloud.
You want to be able to manage the code without needing to provision and manage your own cluster. What should you do?

A. Migrate the Spark jobs to Dataproc on Google Kubernetes Engine.
B. Migrate the Spark jobs to Dataproc on Compute Engine.
C. Migrate the Spark jobs to Dataproc Serverless.
D. Configure a Google Kubernetes Engine cluster with Spark operators, and deploy the Spark jobs.

Answer: C

NEW QUESTION # 20
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 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 materialized view that performs a union across all of the regional sales tables. Use the rank() window function to query the new materialized view.

Answer: D

NEW QUESTION # 21
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 Dataform workflows.
C. Use Dataflow pipelines.
D. Use Cloud Composer operators.

Answer: B

NEW QUESTION # 22
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