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Google ADP Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Pipeline Orchestration18%- 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. Data transformation requirements
  • 2. ETL vs ELT processes
Topic 2: Data Preparation and Ingestion30%- 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
- Data loading methods
  • 1. gcloud, BQ CLI, client libraries
  • 2. Batch and streaming ingestion
- Storage solutions selection
  • 1. Cloud Storage, BigQuery, Cloud SQL, Firestore, Bigtable, Spanner
  • 2. Storage location types: regional, dual-regional, multi-regional, zonal
Topic 3: Data Management and Governance25%- Data security and access control
  • 1. IAM roles and permissions
  • 2. Data encryption and protection
- 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
Topic 4: Data Analysis and Presentation27%- Data visualization and reporting
  • 1. Visualization best practices
  • 2. Looker dashboards and reports
- Data exploration and analysis
  • 1. Jupyter notebooks for analysis
  • 2. BigQuery SQL queries
  • 3. Identify trends, patterns, insights
- Business intelligence and decision support
  • 1. Communicate findings effectively
  • 2. Answer business questions with data

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Google Associate Data Practitioner Sample Questions (Q18-Q23):

NEW QUESTION # 18
You used BigQuery ML to build a customer purchase propensity model six months ago. You want to compare the current serving data with the historical serving data to determine whether you need to retrain the model.
What should you do?

Answer: A


NEW QUESTION # 19
Your organization plans to move their on-premises environment to Google Cloud. Your organization's network bandwidth is less than 1 Gbps. You need to move over 500 ## of data to Cloud Storage securely, and only have a few days to move the dat a. What should you do?

Answer: C


NEW QUESTION # 20
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?

Answer: C


NEW QUESTION # 21
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?

Answer: C


NEW QUESTION # 22
You are working with a small dataset in Cloud Storage that needs to be transformed and loaded into BigQuery for analysis. The transformation involves simple filtering and aggregation operations. You want to use the most efficient and cost-effective data manipulation approach. What should you do?

Answer: C


NEW QUESTION # 23
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