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Google ADP Exam Syllabus Topics:

SectionWeightObjectives
Data Analysis and Presentation27%- Querying and analyzing data
  • 1. BigQuery SQL usage
    • 2. Data aggregation and transformation
      - Data visualization
      • 1. Looker / Looker Studio reporting
        Data Preparation and Ingestion30%- Data ingestion into Google Cloud services
        • 1. Streaming ingestion with Pub/Sub concepts
          • 2. Cloud Storage ingestion patterns
            Data Management25%- Storage and data organization
            • 1. Cloud Storage lifecycle policies
              • 2. BigQuery datasets and tables management
                - Data governance and security
                • 1. IAM and access control
                  • 2. Data lifecycle management
                    Data Pipeline Orchestration18%- Pipeline design and automation
                    • 1. Dataflow pipelines
                      • 2. Workflow orchestration concepts (e.g., Cloud Composer)

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                        Google Associate Data Practitioner Sample Questions (Q19-Q24):

                        NEW QUESTION # 19
                        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: D


                        NEW QUESTION # 20
                        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?

                        Answer: C


                        NEW QUESTION # 21
                        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: B


                        NEW QUESTION # 22
                        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?

                        Answer: D


                        NEW QUESTION # 23
                        You work for an ecommerce company that has a BigQuery dataset that contains customer purchase history, demographics, and website interactions. You need to build a machine learning (ML) model to predict which customers are most likely to make a purchase in the next month. You have limited engineering resources and need to minimize the ML expertise required for the solution. What should you do?

                        Answer: C


                        NEW QUESTION # 24
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