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Google GCP-DE Exam Syllabus Topics:

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

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                                  Google Data Engineer Sample Questions (Q47-Q52):

                                  NEW QUESTION # 47
                                  Cloud Dataproc is a managed Apache Hadoop and Apache service.

                                  Answer: A

                                  Explanation:
                                  Cloud Dataproc is a managed Apache Spark and Apache Hadoop service that lets you use open source data tools for batch processing, querying, streaming, and machine learning.
                                  Reference: https://cloud.google.com/dataproc/docs/


                                  NEW QUESTION # 48
                                  You have a data pipeline with a Cloud Dataflow job that aggregates and writes time series metrics to Cloud Bigtable. This data feeds a dashboard used by thousands of users across the organization. You need to support additional concurrent users and reduce the amount of time required to write the dat a. Which two actions should you take? (Choose two.)

                                  Answer: C,D


                                  NEW QUESTION # 49
                                  Which of these sources can you not load data into BigQuery from?

                                  Answer: D

                                  Explanation:
                                  You can load data into BigQuery from a file upload, Google Cloud Storage, Google Drive, or Google Cloud Bigtable. It is not possible to load data into BigQuery directly from Google Cloud SQL. One way to get data from Cloud SQL to BigQuery would be to export data from Cloud SQL to Cloud Storage and then load it from there.
                                  Reference: https://cloud.google.com/bigquery/loading-data


                                  NEW QUESTION # 50
                                  Your company is loading comma-separated values (CSV) files into Google BigQuery. The data is fully imported successfully; however, the imported data is not matching byte-to-byte to the source file. What is the most likely cause of this problem?

                                  Answer: D


                                  NEW QUESTION # 51
                                  What are the minimum permissions needed for a service account used with Google Dataproc?

                                  Answer: B

                                  Explanation:
                                  Service accounts authenticate applications running on your virtual machine instances to other Google Cloud Platform services. For example, if you write an application that reads and writes files on Google Cloud Storage, it must first authenticate to the Google Cloud Storage API. At a minimum, service accounts used with Cloud Dataproc need permissions to read and write to Google Cloud Storage, and to write to Google Cloud Logging.
                                  Reference: https://cloud.google.com/dataproc/docs/concepts/service-accounts#important_notes


                                  NEW QUESTION # 52
                                  ......

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