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Google ADP Exam Syllabus Topics:

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

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Google ADP Latest Test Questions - ADP Free Vce Dumps

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Google Associate Data Practitioner Sample Questions (Q11-Q16):

NEW QUESTION # 11
Your organization has decided to migrate their existing enterprise data warehouse to BigQuery. The existing data pipeline tools already support connectors to BigQuery. You need to identify a data migration approach that optimizes migration speed. What should you do?

A. Create a temporary file system to facilitate data transfer from the existing environment to Cloud Storage. Use Storage Transfer Service to migrate the data into BigQuery.
B. Use the BigQuery Data Transfer Service to recreate the data pipeline and migrate the data into BigQuery.
C. Use the existing data pipeline tool's BigQuery connector to reconfigure the data mapping.
D. Use the Cloud Data Fusion web interface to build data pipelines. Create a directed acyclic graph (DAG) that facilitates pipeline orchestration.

Answer: C

NEW QUESTION # 12
Your organization has a BigQuery dataset that contains sensitive employee information such as salaries and performance reviews. The payroll specialist in the HR department needs to have continuous access to aggregated performance data, but they do not need continuous access to other sensitive dat a. You need to grant the payroll specialist access to the performance data without granting them access to the entire dataset using the simplest and most secure approach. What should you do?

A. Create a table with the aggregated performance data. Use table-level permissions to grant access to the payroll specialist.
B. Create row-level and column-level permissions and policies on the table that contains performance data in the dataset. Provide the payroll specialist with the appropriate permission set.
C. Create a SQL query with the aggregated performance data. Export the results to an Avro file in a Cloud Storage bucket. Share the bucket with the payroll specialist.
D. Use authorized views to share query results with the payroll specialist.

Answer: D

NEW QUESTION # 13
You recently inherited a task for managing Dataflow streaming pipelines in your organization and noticed that proper access had not been provisioned to you. You need to request a Google-provided IAM role so you can restart the pipelines. You need to follow the principle of least privilege. What should you do?

A. Request the Dataflow Viewer role.
B. Request the Dataflow Worker role.
C. Request the Dataflow Admin role.
D. Request the Dataflow Developer role.

Answer: D

NEW QUESTION # 14
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. Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the --no- clobber option.
B. Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the -- daisy-chain option.
C. Use Storage Transfer Service to configure an agent-based transfer. Set the appropriate bandwidth limit for the agent pool.
D. Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google Cloud.

Answer: C

NEW QUESTION # 15
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. Use Cloud Run functions to trigger data validation and cleaning routines when new data arrives in Cloud Storage.
D. 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.

Answer: A

NEW QUESTION # 16
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