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The Google ADP certification exam is one of the hottest and career-oriented Associate Data Practitioner (ADP) exams. With the Associate Data Practitioner (ADP) exam you can validate your skills and upgrade your knowledge level. By doing this you can learn new in-demand skills and gain multiple career opportunities. To do this you just need to enroll in the Google ADP Certification Exam and put all your efforts to pass this important Google ADP Exam Questions.
| Section | Weight | Objectives |
|---|
| Data Preparation and Ingestion | 30% | - Data formats and classification
- 1. Structured, semi-structured, unstructured data
- 2. Formats: CSV, JSON, Parquet, Avro, database tables
- Data extraction and transfer tools
- 1. Cloud Data Fusion, Storage Transfer Service
- 2. Dataflow, BigQuery Data Transfer Service, Database Migration Service
- Storage solutions selection
- 1. Storage location types: regional, dual-regional, multi-regional, zonal
- 2. Cloud Storage, BigQuery, Cloud SQL, Firestore, Bigtable, Spanner
- Data loading methods
- 1. Batch and streaming ingestion
- 2. gcloud, BQ CLI, client libraries
|
| Data Analysis and Presentation | 27% | - Data visualization and reporting
- 1. Visualization best practices
- 2. Looker dashboards and reports
- Business intelligence and decision support
- 1. Answer business questions with data
- 2. Communicate findings effectively
- Data exploration and analysis
- 1. BigQuery SQL queries
- 2. Jupyter notebooks for analysis
- 3. Identify trends, patterns, insights
|
| Data Pipeline Orchestration | 18% | - Data transformation concepts
- 1. ETL vs ELT processes
- 2. Data transformation requirements
- 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 Management and Governance | 25% | - Data quality and maintenance
- 1. Data lifecycle management
- 2. Data validation and cleaning
- Compliance and governance
- 1. Data privacy and regulatory requirements
- 2. Data stewardship and cataloging
- Data security and access control
- 1. IAM roles and permissions
- 2. Data encryption and protection
|
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Google Associate Data Practitioner Sample Questions (Q15-Q20):
NEW QUESTION # 15
Your company is building a near real-time streaming pipeline to process JSON telemetry data from small appliances. You need to process messages arriving at a Pub/Sub topic, capitalize letters in the serial number field, and write results to BigQuery. You want to use a managed service and write a minimal amount of code for underlying transformations. What should you do?
- A. Use a Pub/Sub push subscription, write a Cloud Run service that accepts the messages, performs the transformations, and writes the results to BigQuery.
- B. Use the "Pub/Sub to BigQuery" Dataflow template with a UDF, and write the results to BigQuery.
- C. Use a Pub/Sub to Cloud Storage subscription, write a Cloud Run service that is triggered when objects arrive in the bucket, performs the transformations, and writes the results to BigQuery.
- D. Use a Pub/Sub to BigQuery subscription, write results directly to BigQuery, and schedule a transformation query to run every five minutes.
Answer: B
NEW QUESTION # 16
You have created a LookML model and dashboard that shows daily sales metrics for five regional managers to use. You want to ensure that the regional managers can only see sales metrics specific to their region. You need an easy-to-implement solution. What should you do?
- A. Create asales_regionuser attribute, and assign each manager's region as the value of their user attribute.
- B. Add anaccess_filterExplore filter on theregion_namedimension by using thesales_regionuser attribute.
- C. Create separate Looker dashboards for each regional manager. Set the default dashboard filter to the corresponding region for each manager.
- D. Create five different Explores with thesql_always_filterExplore filter applied on theregion_namedimension. Set eachregion_namevalue to the corresponding region for each manager.
Answer: A
NEW QUESTION # 17
You need to create a weekly aggregated sales report based on a large volume of data. You want to use Python to design an efficient process for generating this report. What should you do?
- A. Create a Colab Enterprise notebook and use the bigframes.pandas library. Schedule the notebook to execute once a week.
- B. Create a Cloud Data Fusion and Wrangler flow. Schedule the flow to run once a week.
- C. Create a Dataflow directed acyclic graph (DAG) coded in Python. Use Cloud Scheduler to schedule the code to run once a week.
- D. Create a Cloud Run function that uses NumPy. Use Cloud Scheduler to schedule the function to run once a week.
Answer: C
NEW QUESTION # 18
You need to create a new data pipeline. You want a serverless solution that meets the following requirements:
* Data is streamed from Pub/Sub and is processed in real-time.
* Data is transformed before being stored.
* Data is stored in a location that will allow it to be analyzed with SQL using Looker.
Which Google Cloud services should you recommend for the pipeline?
- A. Cloud Composer Cloud SQL for MySQL
- B. BigQuery Analytics Hub
- C. Dataproc Serverless Bigtable
- D. Dataflow BigQuery
Answer: D
NEW QUESTION # 19
You created a customer support application that sends several forms of data to Google Cloud. Your application is sending:
1. Audio files from phone interactions with support agents that will be accessed during trainings.
2. CSV files of users' personally identifiable information (PII) that will be analyzed with SQL.
3. A large volume of small document files that will power other applications.
You need to select the appropriate tool for each data type given the required use case, while following Google- recommended practices. Which should you choose?
- A. Filestore Bigtable BigQuery
- B. Filestore Cloud SQL for PostgreSQL Datastore
- C. Cloud Storage BigQuery Firestore
- D. Cloud Storage CloudSQL for PostgreSQL Bigtable
Answer: C
NEW QUESTION # 20
......
Certification has become a prerequisite for employment and career growth in the Google industry for reputable companies. To advance comfortably in your career, passing the ADP exam is a valuable validation of your expertise. However, many test takers struggle to find updated Associate Data Practitioner (ADP) dumps and fail to prepare effectively in a short period, resulting in a loss of time, money, and motivation.
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