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Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Pipeline Orchestration	18%	- Pipeline design and automation 1. Workflow orchestration concepts (e.g., Cloud Composer) 2. Dataflow pipelines
Topic 2: 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
Topic 3: Data Management	25%	- Storage and data organization 1. Cloud Storage lifecycle policies 2. BigQuery datasets and tables management - Data governance and security 1. Data lifecycle management 2. IAM and access control
Topic 4: 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 (Q39-Q44):

NEW QUESTION # 39
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 materialized view in BigQuery that uses the SUM() function and the DATE_SUB() function.
B. Create a BigQuery table that uses the SUM() function and the _PARTITIONDATE filter.
C. Create a BigQuery table that uses the SUM() function and the DATE_DIFF() function.
D. 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.

Answer: A

NEW QUESTION # 40
Following a recent company acquisition, you inherited an on- premises data infrastructure that needs to move to Google Cloud. The acquired system has 250 Apache Airflow directed acyclic graphs (DAGs) orchestrating data pipelines. You need to migrate the pipelines to a Google Cloud managed service with minimal effort. What should you do?

A. Create a new Cloud Composer environment and copy DAGS to the Cloud Composer dags/folder.
B. Create a Google Kubernetes Engine (GKE) standard cluster and deploy Airflow as a workload. Migrate all DAGs to the new Airflow environment.
C. Create a Cloud Data Fusion instance. For each DAG, create a Cloud Data Fusion pipeline.
D. Convert each DAG to a Cloud Workflow and automate the execution with Cloud Scheduler.

Answer: A

NEW QUESTION # 41
You are migrating data from a legacy on-premises MySQL database to Google Cloud. The database contains various tables with different data types and sizes, including large tables with millions of rows and transactional dat a. You need to migrate this data while maintaining data integrity, and minimizing downtime and cost. What should you do?

A. Use Database Migration Service to replicate the MySQL database to a Cloud SQL for MySQL instance.
B. Set up a Cloud Composer environment to orchestrate a custom data pipeline. Use a Python script to extract data from the MySQL database and load it to MySQL on Compute Engine.
C. Export the MySQL database to CSV files, transfer the files to Cloud Storage by using Storage Transfer Service, and load the files into a Cloud SQL for MySQL instance.
D. Use Cloud Data Fusion to migrate the MySQL database to MySQL on Compute Engine.

Answer: A

NEW QUESTION # 42
Your organization's website uses an on-premises MySQL as a backend database. You need to migrate the on-premises MySQL database to Google Cloud while maintaining MySQL features. You want to minimize administrative overhead and downtime. What should you do?

A. Use a Google-provided Dataflow template to replicate the MySQL database in BigQuery.
B. Install MySQL on a Compute Engine virtual machine. Export the database files using the mysqldump command. Upload the files to Cloud Storage, and import them into the MySQL instance on Compute Engine.
C. Export the database tables to CSV files, and upload the files to Cloud Storage. Convert the MySQL schema to a Spanner schema, create a JSON manifest file, and run a Google-provided Dataflow template to load the data into Spanner.
D. Use Database Migration Service to transfer the data to Cloud SQL for MySQL, and configure the on premises MySQL database as the source.

Answer: D

NEW QUESTION # 43
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 a Transfer Appliance.
B. Use Cloud Storage FUSE.
C. Use gcloud storage commands.
D. Use Storage Transfer Service.

Answer: D

NEW QUESTION # 44
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