Quiz Latest GCP-DE - Data Engineer Exam Simulations

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Google GCP-DE Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Managing and optimizing solutions20%-25%- Reliability and scalability
  • 1. Implement disaster recovery strategies
  • 2. Scale data workloads efficiently
  • 3. Design highly available systems
- Managing resources and costs
  • 1. Optimize storage and compute usage
  • 2. Tune query and pipeline performance
  • 3. Control operational costs
Topic 2: Building and operationalizing data processing systems28%-33%- Operationalizing systems
  • 1. Monitor data pipelines and workloads
  • 2. Manage logging and alerting
  • 3. Implement fault tolerance and recovery
- Building data processing systems
  • 1. Implement streaming data systems
  • 2. Use BigQuery, Dataflow, Pub/Sub, Dataproc and related services
  • 3. Implement batch processing systems
Topic 3: Designing data processing systems22%-27%- Designing for data ingestion
  • 1. Design batch and streaming ingestion solutions
  • 2. Select appropriate storage systems
  • 3. Design scalable and reliable ingestion architecture
- Designing data pipelines
  • 1. Design orchestration workflows
  • 2. Build ETL and ELT pipelines
  • 3. Optimize pipeline performance and cost
Topic 4: Ensuring solution quality20%-25%- Security and compliance
  • 1. Implement encryption and compliance controls
  • 2. Manage IAM and access control
  • 3. Protect sensitive data
- Data quality management
  • 1. Maintain metadata and lineage
  • 2. Validate and clean data
  • 3. Implement data governance

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Google Data Engineer Sample Questions (Q32-Q37):

NEW QUESTION # 32
You are developing an application on Google Cloud that will automatically generate subject labels for users' blog posts. You are under competitive pressure to add this feature quickly, and you have no additional developer resources. No one on your team has experience with machine learning. What should you do?

Answer: A


NEW QUESTION # 33
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: D


NEW QUESTION # 34
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: C


NEW QUESTION # 35
Cloud Dataproc is a managed Apache Hadoop and Apache service.

Answer: B

Explanation:
Cloud Dataproc is a managed Apache Spark and Apache Hadoop service that lets you use open source data tools for batch processing, querying, streaming, and machine learning.
Reference: https://cloud.google.com/dataproc/docs/


NEW QUESTION # 36
You are selecting services to write and transform JSON messages from Cloud Pub/Sub to BigQuery for a data pipeline on Google Cloud. You want to minimize service costs. You also want to monitor and accommodate input data volume that will vary in size with minimal manual intervention. What should you do?

Answer: G


NEW QUESTION # 37
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