ADP Latest Test Discount | ADP Exam Outline

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Google ADP Exam Syllabus Topics:

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

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Associate Data Practitioner updated study torrent & ADP valid test pdf & Associate Data Practitioner training guide dumps

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Google Associate Data Practitioner Sample Questions (Q64-Q69):

NEW QUESTION # 64
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 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.
B. Create a table with the aggregated performance data. Use table-level permissions to grant access to the payroll specialist.
C. Use authorized views to share query results with the payroll specialist.
D. 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.

Answer: C

NEW QUESTION # 65
You need to transfer approximately 300 TB of data from your company's on-premises data center to Cloud Storage. You have 100 Mbps internet bandwidth, and the transfer needs to be completed as quickly as possible. What should you do?

A. Use Cloud Client Libraries to transfer the data over the internet.
B. Use the gcloud storage command to transfer the data over the internet.
C. Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google.
D. Compress the data, upload it to multiple cloud storage providers, and then transfer the data to CloudStorage.

Answer: C

NEW QUESTION # 66
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 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.
B. Create a materialized view in BigQuery that uses the SUM() function and the DATE_SUB() function.
C. Create a BigQuery table that uses the SUM() function and the DATE_DIFF() function.
D. Create a BigQuery table that uses the SUM() function and the _PARTITIONDATE filter.

Answer: B

NEW QUESTION # 67
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. Use the BigQuery Data Transfer Service to recreate the data pipeline and migrate the data into BigQuery.
B. 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.
C. Use the Cloud Data Fusion web interface to build data pipelines. Create a directed acyclic graph (DAG) that facilitates pipeline orchestration.
D. Use the existing data pipeline tool's BigQuery connector to reconfigure the data mapping.

Answer: D

NEW QUESTION # 68
You work for a healthcare company. You have a daily ETL pipeline that extracts patient data from a legacy system, transforms it, and loads it into BigQuery for analysis. The pipeline currently runs manually using a shell script. You want to automate this process and add monitoring to ensure pipeline observability and troubleshooting insights. You want one centralized solution, using open-source tooling, without rewriting the ETL code. What should you do?

A. Configure Cloud Dataflow to implement the ETL pipeline, and use Cloud Scheduler to trigger the Dataflow pipeline daily. Monitor the pipelines execution using the Dataflow job monitoring interface and Cloud Monitoring.
B. Use Cloud Scheduler to trigger a Dataproc job to execute the pipeline daily. Monitor the job's progress using the Dataproc job web interface and Cloud Monitoring.
C. Create a Cloud Run function that runs the pipeline daily. Monitor the functions execution using Cloud Monitoring.
D. Create a direct acyclic graph (DAG) in Cloud Composer to orchestrate a pipeline trigger daily. Monitor the pipeline's execution using the Apache Airflow web interface and Cloud Monitoring.

Answer: D

NEW QUESTION # 69
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