Professional-Data-Engineer Exams Dumps & Valid Professional-Data-Engineer Study Materials

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Google Professional-Data-Engineer Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Ensuring solution quality28%- Reliability and performance
  • 1. Monitoring pipelines and workloads
    • 2. Fault tolerance and recovery strategies
      - Security and governance
      • 1. Data governance and compliance
        • 2. IAM and access control in GCP
          Topic 2: Operationalizing machine learning models26%- ML pipeline integration
          • 1. Vertex AI pipeline deployment
            • 2. Feature engineering and feature stores
              - Model deployment and monitoring
              • 1. Model monitoring and drift detection
                • 2. Online vs batch prediction
                  Topic 3: Building and operationalizing data processing systems24%- Data ingestion and integration
                  • 1. Batch ingestion pipelines (BigQuery, Cloud Storage)
                    • 2. Streaming ingestion (Pub/Sub, Dataflow)
                      - Data processing and transformation
                      • 1. Using Dataproc, Dataflow, and BigQuery SQL
                        • 2. ETL/ELT pipeline design
                          Topic 4: Designing data processing systems22%- Batch and streaming data processing design
                          • 1. Latency, throughput, and consistency trade-offs
                            • 2. Event-driven vs batch architectures
                              - Data architecture and storage design
                              • 1. Designing scalable and cost-effective data models
                                • 2. Choosing appropriate data storage solutions (relational, NoSQL, data warehouse)

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                                  Google Certified Professional Data Engineer Exam Sample Questions (Q413-Q418):

                                  NEW QUESTION # 413
                                  Your company is performing data preprocessing for a learning algorithm in Google Cloud Dataflow. Numerous data logs are being are being generated during this step, and the team wants to analyze them. Due to the dynamic nature of the campaign, the data is growing exponentially every hour.
                                  The data scientists have written the following code to read the data for a new key features in the logs.
                                  BigQueryIO.Read
                                  .named("ReadLogData")
                                  .from("clouddataflow-readonly:samples.log_data")
                                  You want to improve the performance of this data read. What should you do?

                                  Answer: C


                                  NEW QUESTION # 414
                                  You are creating a model to predict housing prices. Due to budget constraints, you must run it on a single resource-constrained virtual machine. Which learning algorithm should you use?

                                  Answer: B

                                  Explanation:
                                  Forecasting and Liner regression is used for predicting housing price.


                                  NEW QUESTION # 415
                                  Your company is in a highly regulated industry. One of your requirements is to ensure individual users have access only to the minimum amount of information required to do their jobs. You want to enforce this requirement with Google BigQuery. Which three approaches can you take? (Choose three.)

                                  Answer: C,D,F

                                  Explanation:
                                  Topic 1, Main Questions Set C


                                  NEW QUESTION # 416
                                  When using Cloud Dataproc clusters, you can access the YARN web interface by configuring a browser to connect through a ____ proxy.

                                  Answer: C

                                  Explanation:
                                  Explanation
                                  When using Cloud Dataproc clusters, configure your browser to use the SOCKS proxy. The SOCKS proxy routes data intended for the Cloud Dataproc cluster through an SSH tunnel.
                                  Reference: https://cloud.google.com/dataproc/docs/concepts/cluster-web-interfaces#interfaces


                                  NEW QUESTION # 417
                                  Your company is implementing a data warehouse using BigQuery, and you have been tasked with designing the data model. You move your on-premises sales data warehouse with a star data schema to BigQuery but notice performance issues when querying the data of the past 30 days Based on Google's recommended practices, what should you do to speed up the query without increasing storage costs?

                                  Answer: A

                                  Explanation:
                                  Star schema is supported by Big Query but is not the most efficient form, if you should design a schema from scratch google recommend to use nested and repeated fields.
                                  In this case, you already have done a migration of the schema and data, so it sounds good and with less effort to do partitioning by transaction date than to redesign the schema.
                                  And other aspect to consider is that this is a data warehouse, so is sure that there is an ETL process and if you change the schema you must adapt the ETL process.


                                  NEW QUESTION # 418
                                  ......

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