Valid Google ADP Exam Test - ADP Pass Test

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Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Preparation and Ingestion	30%	- Data extraction and transfer tools 1. Dataflow, BigQuery Data Transfer Service, Database Migration Service 2. Cloud Data Fusion, Storage Transfer Service - Data loading methods 1. Batch and streaming ingestion 2. gcloud, BQ CLI, client libraries - Data formats and classification 1. Formats: CSV, JSON, Parquet, Avro, database tables 2. Structured, semi-structured, unstructured data - Storage solutions selection 1. Cloud Storage, BigQuery, Cloud SQL, Firestore, Bigtable, Spanner 2. Storage location types: regional, dual-regional, multi-regional, zonal
Topic 2: Data Management and Governance	25%	- Compliance and governance 1. Data privacy and regulatory requirements 2. Data stewardship and cataloging - Data security and access control 1. Data encryption and protection 2. IAM roles and permissions - Data quality and maintenance 1. Data lifecycle management 2. Data validation and cleaning
Topic 3: Data Pipeline Orchestration	18%	- Transformation tools selection 1. Dataproc, Dataflow, Cloud Data Fusion, Cloud Composer, Dataform - Pipeline automation and scheduling 1. Schedule and monitor data jobs 2. Error handling and monitoring - Data transformation concepts 1. ETL vs ELT processes 2. Data transformation requirements
Topic 4: Data Analysis and Presentation	27%	- Data visualization and reporting 1. Visualization best practices 2. Looker dashboards and reports - Business intelligence and decision support 1. Communicate findings effectively 2. Answer business questions with data - Data exploration and analysis 1. Jupyter notebooks for analysis 2. BigQuery SQL queries 3. Identify trends, patterns, insights

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Google Associate Data Practitioner Sample Questions (Q45-Q50):

NEW QUESTION # 45
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 existing data pipeline tool's BigQuery connector to reconfigure the data mapping.
B. Use the BigQuery Data Transfer Service to recreate the data pipeline and 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. 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.

Answer: A

NEW QUESTION # 46
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. 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.
C. Use Cloud Data Fusion to migrate the MySQL database to MySQL on Compute Engine.
D. 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.

Answer: A

NEW QUESTION # 47
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. Use authorized views to share query results with 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. Create a table with the aggregated performance data. Use table-level permissions to grant access to the payroll specialist.

Answer: A

NEW QUESTION # 48
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 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. Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the --no- clobber option.

Answer: C

NEW QUESTION # 49
Your organization uses Dataflow pipelines to process real-time financial transactions. You discover that one of your Dataflow jobs has failed. You need to troubleshoot the issue as quickly as possible. What should you do?

A. Use the gcloud CLI tool to retrieve job metrics and logs, and analyze them for errors and performance bottlenecks.
B. Create a custom script to periodically poll the Dataflow API for job status updates, and send email alerts if any errors are identified.
C. Set up a Cloud Monitoring dashboard to track key Dataflow metrics, such as data throughput, error rates, and resource utilization.
D. Navigate to the Dataflow Jobs page in the Google Cloud console. Use the job logs and worker logs to identify the error.

Answer: D

NEW QUESTION # 50
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