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

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Google Associate Data Practitioner Sample Questions (Q27-Q32):

NEW QUESTION # 27
Your organization uses a BigQuery table that is partitioned by ingestion time. You need to remove data that is older than one year to reduce your organization's storage costs. You want to use the most efficient approach while minimizing cost. What should you do?

A. Require users to specify a partition filter using the alter table statement in SQL.
B. Set the table partition expiration period to one year using the ALTER TABLE statement in SQL.
C. Create a view that filters out rows that are older than one year.
D. Create a scheduled query that periodically runs an update statement in SQL that sets the "deleted" column to "yes" for data that is more than one year old. Create a view that filters out rows that have been marked deleted.

Answer: B

NEW QUESTION # 28
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 Google Kubernetes Engine (GKE) standard cluster and deploy Airflow as a workload. Migrate all DAGs to the new Airflow environment.
B. Create a Cloud Data Fusion instance. For each DAG, create a Cloud Data Fusion pipeline.
C. Convert each DAG to a Cloud Workflow and automate the execution with Cloud Scheduler.
D. Create a new Cloud Composer environment and copy DAGS to the Cloud Composer dags/folder.

Answer: D

NEW QUESTION # 29
Your company has an on-premises file server with 5 TB of data that needs to be migrated to Google Cloud.
The network operations team has mandated that you can only use up to 250 Mbps of the total available bandwidth for the migration. You need to perform an online migration to Cloud Storage. What should you do?

A. Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google Cloud.
B. Use Storage Transfer Service to configure an agent-based transfer. Set the appropriate bandwidth limit for the agent pool.
C. Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the -- daisy-chain option.
D. Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the --no- clobber option.

Answer: B

NEW QUESTION # 30
You are working on a data pipeline that will validate and clean incoming data before loading it into BigQuery for real-time analysis. You want to ensure that the data validation and cleaning is performed efficiently and can handle high volumes of dat a. What should you do?

A. Use Dataflow to create a streaming pipeline that includes validation and transformation steps.
B. Write custom scripts in Python to validate and clean the data outside of Google Cloud. Load the cleaned data into BigQuery.
C. Load the raw data into BigQuery using Cloud Storage as a staging area, and use SQL queries in BigQuery to validate and clean the data.
D. Use Cloud Run functions to trigger data validation and cleaning routines when new data arrives in Cloud Storage.

Answer: A

NEW QUESTION # 31
Your company stores historical data in Cloud Storage. You need to ensure that all data is saved in a bucket for at least three years. What should you do?

A. Change the bucket storage class to Archive.
B. Enable Object Versioning.
C. Set a bucket retention policy.
D. Set temporary object holds.

Answer: C

NEW QUESTION # 32
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