Google GCP-DE Reliable Exam Simulations - GCP-DE Reliable Test Pdf

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Google GCP-DE Exam Syllabus Topics:

SectionWeightObjectives
Storing and managing data20%- Optimizing storage performance and cost
  • 1. Implementing cost optimization strategies
  • 2. Configuring storage for access patterns
- Implementing storage solutions
  • 1. Designing data warehouses and data lakes
  • 2. Using data storage services appropriately
  • 3. Managing data lifecycle and retention
Designing data processing systems24%- Planning data solutions
  • 1. Designing for reliability, scalability, and efficiency
  • 2. Planning for data security and compliance
  • 3. Selecting appropriate storage solutions
- Designing data pipelines
  • 1. Designing for data transformation and enrichment
  • 2. Defining architecture for batch and streaming processing
  • 3. Planning for data migration and integration
Maintaining and automating data workloads18%- Automation and optimization
  • 1. Automating deployment and management
  • 2. Optimizing resource usage and costs
- Operationalizing workloads
  • 1. Monitoring and troubleshooting pipelines
  • 2. Ensuring reliability and recoverability
  • 3. Orchestrating and scheduling jobs
Preparing data for analysis and machine learning13%- Enabling data analysis
  • 1. Preparing datasets for querying and reporting
  • 2. Implementing data sharing and governance
  • 3. Optimizing query performance
- Preparing data for ML
  • 1. Supporting model training and serving
  • 2. Feature engineering and data preparation
Ingesting and processing data25%- Building data pipelines
  • 1. Handling data quality and consistency
  • 2. Implementing ingestion mechanisms
  • 3. Developing batch and streaming workflows
- Transforming data
  • 1. Managing schema evolution
  • 2. Applying data processing logic
  • 3. Optimizing transformations for performance

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Google Data Engineer Sample Questions (Q66-Q71):

NEW QUESTION # 66
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,E


NEW QUESTION # 67
When using Cloud Dataproc clusters, you can access the YARN web interface by configuring a browser to connect through a proxy.

Answer: B

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 # 68
You are planning to use Google's Dataflow SDK to analyze customer data such as displayed below. Your project requirement is to extract only the customer name Passing Certification Exams Made Easy visit - https://www.2PassEasy.com from the data source and then write to an output PCollection.
Tom,555 X street Tim,553 Y street Sam, 111 Z street
Which operation is best suited for the above data processing requirement?

Answer: B

Explanation:
In Google Cloud dataflow SDK, you can use the ParDo to extract only a customer name of each element in your PCollection.
Reference: https://cloud.google.com/dataflow/model/par-do


NEW QUESTION # 69
You want to automate execution of a multi-step data pipeline running on Google Cloud. The pipeline includes Cloud Dataproc and Cloud Dataflow jobs that have multiple dependencies on each other. You want to use managed services where possible, and the pipeline will run every day. Which tool should you use?

Answer: A


NEW QUESTION # 70
You have a data stored in BigQuery. The data in the BigQuery dataset must be highly available. You need to define a storage, backup, and recovery strategy of this data that minimizes cost. How should you configure the BigQuery table?

Answer: D


NEW QUESTION # 71
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