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Google GCP-DE Exam Syllabus Topics:

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

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Google Data Engineer Sample Questions (Q47-Q52):

NEW QUESTION # 47
When using Cloud Dataproc clusters, you can access the YARN web interface by configuring a browser to connect through a proxy.

Answer: C

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 # 48
What is the general recommendation when designing your row keys for a Cloud Bigtable schema?

Answer: C

Explanation:
A general guide is to, keep your row keys reasonably short. Long row keys take up additional memory and storage and increase the time it takes to get responses from the Cloud Bigtable server.
Reference: https://cloud.google.com/bigtable/docs/schema-design#row-keys


NEW QUESTION # 49
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 # 50
Each analytics team in your organization is running BigQuery jobs in their own projects. You want to enable each team to monitor slot usage within their projects. What should you do?

Answer: D


NEW QUESTION # 51
Which Google Cloud Platform service is an alternative to Hadoop with Hive?

Answer: A

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 # 52
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