Google GCP-DE Questions: Fosters Your Exam Passing Abilities [2026]

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Google GCP-DE Exam Syllabus Topics:

SectionWeightObjectives
Designing data processing systems20%- Data pipeline architecture design
  • 1. Scalable data ingestion design
    • 2. Batch vs streaming data processing selection
      - Storage and data modeling
      • 1. Data lake architecture on Google Cloud Storage
        • 2. Data warehouse design using BigQuery
          Building and operationalizing data processing systems30%- Data pipeline implementation
          • 1. Dataflow pipeline development
            • 2. Dataproc and Spark-based processing
              - Data ingestion and transformation
              • 1. Pub/Sub streaming ingestion
                • 2. ETL/ELT workflows
                  Maintaining and optimizing data and ML solutions20%- Security and governance
                  • 1. Data encryption and compliance
                    • 2. IAM and access control
                      - Machine learning integration
                      • 1. Vertex AI integration for pipelines
                        • 2. BigQuery ML usage
                          Operationalizing data and ML pipelines30%- Pipeline automation and orchestration
                          • 1. Scheduling and monitoring pipelines
                            • 2. Cloud Composer workflows
                              - Monitoring and troubleshooting
                              • 1. Performance optimization and debugging
                                • 2. Logging and observability

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                                  GCP-DE Preparation, Exam GCP-DE Topic

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                                  Google Data Engineer Sample Questions (Q36-Q41):

                                  NEW QUESTION # 36
                                  MJTelco is building a custom interface to share dat
                                  a. They have these requirements:
                                  They need to do aggregations over their petabyte-scale datasets.
                                  They need to scan specific time range rows with a very fast response time (milliseconds). Which combination of Google Cloud Platform products should you recommend?

                                  Answer: A


                                  NEW QUESTION # 37
                                  You have developed three data processing jobs. One executes a Cloud Dataflow pipeline that transforms data uploaded to Cloud Storage and writes results to BigQuery. The second ingests data from on-premises servers and uploads it to Cloud Storage. The third is a Cloud Dataflow pipeline that gets information from third-party data providers and uploads the information to Cloud Storage. You need to be able to schedule and monitor the execution of these three workflows and manually execute them when needed. What should you do?

                                  Answer: B


                                  NEW QUESTION # 38
                                  You are operating a Cloud Dataflow streaming pipeline. The pipeline aggregates events from a Cloud Pub/Sub subscription source, within a window, and sinks the resulting aggregation to a Cloud Storage bucket. The source has consistent throughput. You want to monitor an alert on behavior of the pipeline with Cloud Stackdriver to ensure that it is processing dat a. Which Stackdriver alerts should you create?

                                  Answer: A


                                  NEW QUESTION # 39
                                  An online retailer has built their current application on Google App Engine. A new initiative at the company mandates that they extend their application to allow their customers to transact directly via the application.
                                  They need to manage their shopping transactions and analyze combined data from multiple datasets using a business intelligence (BI) tool. They want to use only a single database for this purpose. Which Google Cloud database should they choose?

                                  Answer: A


                                  NEW QUESTION # 40
                                  You are building a model to predict whether or not it will rain on a given day. You have thousands of input features and want to see if you can improve training speed by removing some features while having a minimum effect on model accuracy. What can you do?

                                  Answer: D


                                  NEW QUESTION # 41
                                  ......

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