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Google GCP-DE Exam Syllabus Topics:

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

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Google Data Engineer Sample Questions (Q36-Q41):

NEW QUESTION # 36
You work for a shipping company that uses handheld scanners to read shipping labels. Your company has strict data privacy standards that require scanners to only transmit recipients' personally identifiable information (PII) to analytics systems, which violates user privacy rules. You want to quickly build a scalable solution using cloud-native managed services to prevent exposure of PII to the analytics systems. What should you do?

Answer: D


NEW QUESTION # 37
Which of the following statements is NOT true regarding Bigtable access roles?

Answer: C

Explanation:
For Cloud Bigtable, you can configure access control at the project level. For example, you can grant the ability to:
Read from, but not write to, any table within the project.
Read from and write to any table within the project, but not manage instances. Read from and write to any table within the project, and manage instances. Reference: https://cloud.google.com/bigtable/docs/access-control


NEW QUESTION # 38
Which Google Cloud Platform service is an alternative to Hadoop with Hive?

Answer: D

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 # 39
Your company maintains a hybrid deployment with GCP, where analytics are performed on your anonymized customer dat a. The data are imported to Cloud Storage from your data center through parallel uploads to a data transfer server running on GCP. Management informs you that the daily transfers take too long and have asked you to fix the problem. You want to maximize transfer speeds. Which action should you take?

Answer: B


NEW QUESTION # 40
What are the minimum permissions needed for a service account used with Google Dataproc?

Answer: B

Explanation:
Service accounts authenticate applications running on your virtual machine instances to other Google Cloud Platform services. For example, if you write an application that reads and writes files on Google Cloud Storage, it must first authenticate to the Google Cloud Storage API. At a minimum, service accounts used with Cloud Dataproc need permissions to read and write to Google Cloud Storage, and to write to Google Cloud Logging.
Reference: https://cloud.google.com/dataproc/docs/concepts/service-accounts#important_notes


NEW QUESTION # 41
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