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Google GCP-DE Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: 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
          Topic 2: Building and operationalizing data processing systems30%- Data ingestion and transformation
          • 1. Pub/Sub streaming ingestion
            • 2. ETL/ELT workflows
              - Data pipeline implementation
              • 1. Dataproc and Spark-based processing
                • 2. Dataflow pipeline development
                  Topic 3: 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
                          Topic 4: Maintaining and optimizing data and ML solutions20%- Security and governance
                          • 1. IAM and access control
                            • 2. Data encryption and compliance
                              - Machine learning integration
                              • 1. BigQuery ML usage
                                • 2. Vertex AI integration for pipelines

                                  Google Data Engineer Sample Questions:

                                  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.)

                                  • A. Configure your Cloud Dataflow pipeline to use local execution
                                  • B. Increase the number of nodes in the Cloud Bigtable cluster
                                  • C. Modify your Cloud Dataflow pipeline to use the CoGroupByKey transform before writing to Cloud Bigtable
                                  • D. Modify your Cloud Dataflow pipeline to use the Flatten transform before writing to Cloud Bigtable
                                  • E. Increase the maximum number of Cloud Dataflow workers by setting maxNumWorkers in PipelineOptions
                                  Reveal Solution  Discussion  0

                                  Correct Answer: C,D  🗳️

                                  You have enabled the free integration between Firebase Analytics and Google BigQuery. Firebase now automatically creates a new table daily in BigQuery in the format app_events_YYYYMMDD. You want to query all of the tables for the past 30 days in legacy SQL. What should you do?

                                  • A. Use the TABLE_DATE_RANGE function
                                  • B. Use the WHERE_PARTITIONTIME pseudo column
                                  • C. Use SELECT IF.(date >= YYYY-MM-DD AND date <= YYYY-MM-DD
                                  • D. Use WHERE date BETWEEN YYYY-MM-DD AND YYYY-MM-DD
                                  Reveal Solution  Discussion  0

                                  Correct Answer: A  🗳️

                                  Explanation: Only visible for ExamBoosts members. You can sign-up / login (it's free).

                                  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?

                                  • A. BigQuery
                                  • B. Cloud SQL
                                  • C. Cloud Bigtable
                                  • D. Cloud Datastore
                                  Reveal Solution  Discussion  0

                                  Correct Answer: B  🗳️

                                  You are responsible for writing your company's ETL pipelines to run on an Apache Hadoop cluster. The pipeline will require some checkpointing and splitting pipelines. Which method should you use to write the pipelines?

                                  • A. PigLatin using Pig
                                  • B. Python using MapReduce
                                  • C. HiveQL using Hive
                                  • D. Java using MapReduce
                                  Reveal Solution  Discussion  0

                                  Correct Answer: B  🗳️

                                  What are two methods that can be used to denormalize tables in BigQuery?

                                  • A. 1) Use nested repeated fields; 2) Use a partitioned table
                                  • B. 1) Join tables into one table; 2) Use nested repeated fields
                                  • C. 1) Use a partitioned table; 2) Join tables into one table
                                  • D. 1) Split table into multiple tables; 2) Use a partitioned table
                                  Reveal Solution  Discussion  0

                                  Correct Answer: B  🗳️

                                  Explanation: Only visible for ExamBoosts members. You can sign-up / login (it's free).

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