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Google GCP-DE Exam Syllabus Topics:

SectionWeightObjectives
Building and operationalizing data processing systems30%- Data ingestion and transformation
  • 1. ETL/ELT workflows
    • 2. Pub/Sub streaming ingestion
      - Data pipeline implementation
      • 1. Dataproc and Spark-based processing
        • 2. Dataflow pipeline development
          Maintaining and optimizing data and ML solutions20%- Security and governance
          • 1. IAM and access control
            • 2. Data encryption and compliance
              - 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
                          Designing data processing systems20%- Storage and data modeling
                          • 1. Data warehouse design using BigQuery
                            • 2. Data lake architecture on Google Cloud Storage
                              - Data pipeline architecture design
                              • 1. Batch vs streaming data processing selection
                                • 2. Scalable data ingestion design

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                                  Google Data Engineer Sample Questions (Q16-Q21):

                                  NEW QUESTION # 16
                                  Which of these sources can you not load data into BigQuery from?

                                  Answer: A

                                  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 # 17
                                  You work for a manufacturing company that sources up to 750 different components, each from a different supplier. You've collected a labeled dataset that has on average 1000 examples for each unique component. Your team wants to implement an app to help warehouse workers recognize incoming components based on a photo of the component. You want to implement the first working version of this app (as Proof-Of-Concept) within a few working days. What should you do?

                                  Answer: C


                                  NEW QUESTION # 18
                                  You need to choose a database for a new project that has the following requirements:
                                  Fully managed
                                  Able to automatically scale up
                                  Transactionally consistent
                                  Able to scale up to 6 TB
                                  Able to be queried using SQL Which database do you choose?

                                  Answer: D


                                  NEW QUESTION # 19
                                  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 # 20
                                  All Google Cloud Bigtable client requests go through a front-end server they are sent to a Cloud Bigtable node.

                                  Answer: D

                                  Explanation:
                                  In a Cloud Bigtable architecture all client requests go through a front-end server before they are sent to a Cloud Bigtable node.
                                  The nodes are organized into a Cloud Bigtable cluster, which belongs to a Cloud Bigtable instance, which is a container for the cluster. Each node in the cluster handles a subset of the requests to the cluster.
                                  When additional nodes are added to a cluster, you can increase the number of simultaneous requests that the cluster can handle, as well as the maximum throughput for the entire cluster.
                                  Reference: https://cloud.google.com/bigtable/docs/overview


                                  NEW QUESTION # 21
                                  ......

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