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Google ADP Exam Syllabus Topics:

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

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                        Google Associate Data Practitioner 認定 ADP 試験問題 (Q29-Q34):

                        質問 # 29
                        Your organization is conducting analysis on regional sales metrics. Data from each regional sales team is stored as separate tables in BigQuery and updated monthly. You need to create a solution that identifies the top three regions with the highest monthly sales for the next three months. You want the solution to automatically provide up-to-date results. What should you do?

                        正解：A


                        質問 # 30
                        Your team is building several data pipelines that contain a collection of complex tasks and dependencies that you want to execute on a schedule, in a specific order. The tasks and dependencies consist of files in Cloud Storage, Apache Spark jobs, and data in BigQuery. You need to design a system that can schedule and automate these data processing tasks using a fully managed approach. What should you do?

                        正解：B


                        質問 # 31
                        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?

                        正解：A


                        質問 # 32
                        Your organization has several datasets in their data warehouse in BigQuery. Several analyst teams in different departments use the datasets to run queries. Your organization is concerned about the variability of their monthly BigQuery costs. You need to identify a solution that creates a fixed budget for costs associated with the queries run by each department. What should you do?

                        正解：B


                        質問 # 33
                        You need to design a data pipeline to process large volumes of raw server log data stored in Cloud Storage.
                        The data needs to be cleaned, transformed, and aggregated before being loaded into BigQuery for analysis.
                        The transformation involves complex data manipulation using Spark scripts that your team developed. You need to implement a solution that leverages your team's existing skillset, processes data at scale, and minimizes cost. What should you do?

                        正解：B


                        質問 # 34
                        ......

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