GCP-DE Learning Materials: Data Engineer & GCP-DE Questions and Answers

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Google GCP-DE Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Building and operationalizing data processing systems30%- Data ingestion and transformation
  • 1. Pub/Sub streaming ingestion
    • 2. ETL/ELT workflows
      - Data pipeline implementation
      • 1. Dataflow pipeline development
        • 2. Dataproc and Spark-based processing
          Topic 2: 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
                  Topic 3: 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
                          Topic 4: 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 warehouse design using BigQuery
                                • 2. Data lake architecture on Google Cloud Storage

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                                  Google GCP-DE Valid Test Sample - Technical GCP-DE Training

                                  No doubt the Google GCP-DE certification is a valuable credential that offers countless advantages to GCP-DE exam holders. Beginners and experienced professionals can validate their skills and knowledge level with the Data Engineer GCP-DE Exam and earn solid proof of their proven skills.

                                  Google Data Engineer Sample Questions (Q44-Q49):

                                  NEW QUESTION # 44
                                  You receive data files in CSV format monthly from a third party. You need to cleanse this data, but every third month the schema of the files changes. Your requirements for implementing these transformations include:
                                  Executing the transformations on a schedule
                                  Enabling non-developer analysts to modify transformations
                                  Providing a graphical tool for designing transformations
                                  What should you do?

                                  Answer: C


                                  NEW QUESTION # 45
                                  You want to process payment transactions in a point-of-sale application that will run on Google Cloud Platform. Your user base could grow exponentially, but you do not want to manage infrastructure scaling.
                                  Which Google database service should you use?

                                  Answer: A


                                  NEW QUESTION # 46
                                  You are designing the database schema for a machine learning-based food ordering service that will predict what users want to eat. Here is some of the information you need to store:
                                  The user profile: What the user likes and doesn't like to eat
                                  The user account information: Name, address, preferred meal times
                                  The order information: When orders are made, from where, to whom
                                  The database will be used to store all the transactional data of the product. You want to optimize the data schem a. Which Google Cloud Platform product should you use?

                                  Answer: B


                                  NEW QUESTION # 47
                                  You are designing storage for two relational tables that are part of a 10-TB database on Google Cloud. You want to support transactions that scale horizontally. You also want to optimize data for range queries on nonkey columns. What should you do?

                                  Answer: E

                                  Explanation:
                                  Reference: https://cloud.google.com/solutions/data-lifecycle-cloud-platform


                                  NEW QUESTION # 48
                                  Which Google Cloud Platform service is an alternative to Hadoop with Hive?

                                  Answer: A

                                  Explanation:
                                  Apache Hive is a data warehouse software project built on top of Apache Hadoop for providing data summarization, query, and analysis. Google BigQuery is an enterprise data warehouse. Reference: https://en.wikipedia.org/wiki/Apache_Hive


                                  NEW QUESTION # 49
                                  ......

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