Valid free ADP test questions and answers, Google ADP practice test

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Google ADP Exam Syllabus Topics:

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

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Google Associate Data Practitioner Sample Questions (Q25-Q30):

NEW QUESTION # 25
You manage a large amount of data in Cloud Storage, including raw data, processed data, and backups. Your organization is subject to strict compliance regulations that mandate data immutability for specific data types.
You want to use an efficient process to reduce storage costs while ensuring that your storage strategy meets retention requirements. What should you do?

A. Configure lifecycle management rules to transition objects to appropriate storage classes based on access patterns. Set up Object Versioning for all objects to meet immutability requirements.
B. Create a Cloud Run function to periodically check object metadata, and move objects to the appropriate storage class based on age and access patterns. Use object holds to enforce immutability for specific objects.
C. Move objects to different storage classes based on their age and access patterns. Use Cloud Key Management Service (Cloud KMS) to encrypt specific objects with customer-managed encryption keys (CMEK) to meet immutability requirements.
D. Use object holds to enforce immutability for specific objects, and configure lifecycle management rules to transition objects to appropriate storage classes based on age and access patterns.

Answer: D

NEW QUESTION # 26
You manage data at an ecommerce company. You have a Dataflow pipeline that processes order data from Pub/Sub, enriches the data with product information from Bigtable, and writes the processed data to BigQuery for analysis. The pipeline runs continuously and processes thousands of orders every minute. You need to monitor the pipeline's performance and be alerted if errors occur. What should you do?

A. Use Cloud Logging to view the pipeline logs and check for errors. Set up alerts based on specific keywords in the logs.
B. Use Cloud Monitoring to track key metrics. Create alerting policies in Cloud Monitoring to trigger notifications when metrics exceed thresholds or when errors occur.
C. Use the Dataflow job monitoring interface to visually inspect the pipeline graph, check for errors, and configure notifications when critical errors occur.
D. Use BigQuery to analyze the processed data in Cloud Storage and identify anomalies or inconsistencies. Set up scheduled alerts based when anomalies or inconsistencies occur.

Answer: B

NEW QUESTION # 27
Your company is migrating their batch transformation pipelines to Google Cloud. You need to choose a solution that supports programmatic transformations using only SQL. You also want the technology to support Git integration for version control of your pipelines. What should you do?

A. Use Dataflow pipelines.
B. Use Cloud Composer operators.
C. Use Dataform workflows.
D. Use Cloud Data Fusion pipelines.

Answer: C

NEW QUESTION # 28
Your organization is conducting analysis on regional sales metrics. Data from each regional sales team is stored as separate tables in BigQuery and updated monthly. You need to create a solution that identifies the top three regions with the highest monthly sales for the next three months. You want the solution to automatically provide up-to-date results. What should you do?

A. Create a BigQuery table that performs a cross join across all of the regional sales tables. Use the rank() window function to query the new table.
B. Create a BigQuery materialized view that performs a union across all of the regional sales tables. Use the rank() window function to query the new materialized view.
C. Create a BigQuery materialized view that performs a cross join across all of the regional sales tables. Use the row_number() window function to query the new materialized view.
D. Create a BigQuery table that performs a union across all of the regional sales tables. Use the row_number() window function to query the new table.

Answer: B

NEW QUESTION # 29
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. 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.
B. Use a Google-provided Dataflow template to replicate the MySQL database in BigQuery.
C. Use Database Migration Service to transfer the data to Cloud SQL for MySQL, and configure the on premises MySQL database as the source.
D. 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.

Answer: C

NEW QUESTION # 30
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