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Google Professional-Data-Engineer Exam Syllabus Topics:

SectionWeightObjectives
Operationalizing machine learning models20%- Preparing data for ML
  • 1. Feature engineering and data preparation
  • 2. Handling structured and unstructured data
- Deploying and maintaining ML models
  • 1. Optimizing model performance and cost
  • 2. Model serving and monitoring
Maintaining and automating data workloads18%- Resource optimization
  • 1. Choosing appropriate compute and storage options
  • 2. Cost management and resource allocation
- Automation and repeatability
  • 1. Automating deployment and updates
  • 2. Implementing CI/CD for data systems
Ensuring solution quality and reliability17%- Troubleshooting and optimization
  • 1. Optimizing queries and workloads
  • 2. Diagnosing performance issues
- Testing and validating data systems
  • 1. Performance and scalability testing
  • 2. Data quality validation
Designing data processing systems20%- Designing for business requirements
  • 1. Designing for reliability and fault tolerance
  • 2. Designing for scalability and elasticity
  • 3. Selecting appropriate storage solutions
- Designing for regulatory and security requirements
  • 1. Implementing access control and data protection
  • 2. Ensuring data privacy and compliance
Building and operationalizing data processing systems25%- Deploying and managing systems
  • 1. Monitoring and logging data processes
  • 2. Managing infrastructure and resources
- Building data pipelines
  • 1. Orchestrating data workflows
  • 2. Ingesting data from various sources
  • 3. Transforming and cleaning data

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Google Certified Professional Data Engineer Exam Sample Questions (Q62-Q67):

NEW QUESTION # 62
You store historic data in Cloud Storage. You need to perform analytics on the historic dat
a. You want to use a solution to detect invalid data entries and perform data transformations that will not require programming or knowledge of SQL.
What should you do?

Answer: B


NEW QUESTION # 63
Your company is streaming real-time sensor data from their factory floor into Bigtable and they have noticed extremely poor performance. How should the row key be redesigned to improve Bigtable performance on queries that populate real-time dashboards?

Answer: D


NEW QUESTION # 64
A live TV show asks viewers to cast votes using their mobile phones. The event generates a large volume of data during a 3 minute period. You are in charge of the Voting restructure* and must ensure that the platform can handle the load and Hal all votes are processed. You must display partial results write voting is open.
After voting doses you need to count the votes exactly once white optimizing cost. What should you do?

Answer: C


NEW QUESTION # 65
The CUSTOM tier for Cloud Machine Learning Engine allows you to specify the number of which types of cluster nodes?

Answer: D

Explanation:
The CUSTOM tier is not a set tier, but rather enables you to use your own cluster specification. When you use this tier, set values to configure your processing cluster according to these guidelines:
You must set TrainingInput.masterType to specify the type of machine to use for your master node. You may set TrainingInput.workerCount to specify the number of workers to use. You may set TrainingInput.parameterServerCount to specify the number of parameter servers to use. You can specify the type of machine for the master node, but you can't specify more than one master node.
Reference: https://cloud.google.com/ml-engine/docs/training-overview#job_configuration_parameters


NEW QUESTION # 66
When using Cloud Dataproc clusters, you can access the YARN web interface by configuring a browser to connect through a ____ proxy.

Answer: D

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.


NEW QUESTION # 67
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