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Google ADP Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Pipeline Orchestration18%- Data transformation concepts
  • 1. Data transformation requirements
  • 2. ETL vs ELT processes
- Pipeline automation and scheduling
  • 1. Schedule and monitor data jobs
  • 2. Error handling and monitoring
- Transformation tools selection
  • 1. Dataproc, Dataflow, Cloud Data Fusion, Cloud Composer, Dataform
Topic 2: Data Preparation and Ingestion30%- 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
- 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 3: Data Analysis and Presentation27%- Data visualization and reporting
  • 1. Looker dashboards and reports
  • 2. Visualization best practices
- 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
Topic 4: Data Management and Governance25%- 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. Data encryption and protection
  • 2. IAM roles and permissions

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Google Associate Data Practitioner Sample Questions (Q51-Q56):

NEW QUESTION # 51
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?

Answer: A


NEW QUESTION # 52
Your retail company wants to analyze customer reviews to understand sentiment and identify areas for improvement. Your company has a large dataset of customer feedback text stored in BigQuery that includes diverse language patterns, emojis, and slang. You want to build a solution to classify customer sentiment from the feedback text. What should you do?

Answer: C


NEW QUESTION # 53
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?

Answer: D


NEW QUESTION # 54
You have a Dataflow pipeline that processes website traffic logs stored in Cloud Storage and writes the processed data to BigQuery. You noticed that the pipeline is failing intermittently. You need to troubleshoot the issue. What should you do?

Answer: D


NEW QUESTION # 55
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?

Answer: D


NEW QUESTION # 56
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