TOP ADP Exam Quick Prep: Associate Data Practitioner - Valid Google Reliable ADP Exam Dumps

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Google ADP Exam Syllabus Topics:

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

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Google Associate Data Practitioner Sample Questions (Q12-Q17):

NEW QUESTION # 12
You are storing data in Cloud Storage for a machine learning project. The data is frequently accessed during the model training phase, minimally accessed after 30 days, and unlikely to be accessed after 90 days. You need to choose the appropriate storage class for the different stages of the project to minimize cost. What should you do?

A. Store the data in Standard storage during the model training phase. Transition the data to Nearline storage 30 days after model deployment, and to Coldline storage 90 days after model deployment.
B. Store the data in Nearline storage during the model training phase. Transition the data to Archive storage 30 days after model deployment, and to Coldline storage 90 days after model deployment.
C. Store the data in Nearline storage during the model training phase. Transition the data to Coldline storage 30 days after model deployment, and to Archive storage 90 days after model deployment.
D. Store the data in Standard storage during the model training phase. Transition the data to Durable Reduced Availability (DRA) storage 30 days after model deployment, and to Coldline storage 90 days after model deployment.

Answer: A

NEW QUESTION # 13
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 the gcloud storage command to transfer the data over the internet.
B. Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google.
C. Compress the data, upload it to multiple cloud storage providers, and then transfer the data to CloudStorage.
D. Use Cloud Client Libraries to transfer the data over the internet.

Answer: B

NEW QUESTION # 14
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 Cloud Data Fusion instance. For each DAG, create a Cloud Data Fusion pipeline.
B. Create a Google Kubernetes Engine (GKE) standard cluster and deploy Airflow as a workload. Migrate all DAGs to the new Airflow environment.
C. Create a new Cloud Composer environment and copy DAGS to the Cloud Composer dags/folder.
D. Convert each DAG to a Cloud Workflow and automate the execution with Cloud Scheduler.

Answer: C

NEW QUESTION # 15
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. Use a Google-provided Dataflow template to replicate the MySQL database in BigQuery.
B. 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.
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. 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.

Answer: C

NEW QUESTION # 16
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. 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.
C. 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.
D. 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.

Answer: B

NEW QUESTION # 17
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