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Requirements
The certification does not have any official prerequisites. However, it is advised to have at least three years of industry experience with one or more years of expertise in designing and managing different solutions with the use of Google Cloud Platform. It is also required to review the topics of the qualifying exam before sitting for it.
Understanding functional and technical aspects of Google Professional Data Engineer Exam Designing data processing systems
The following will be discussed here:
- Batch and streaming data (e.g., Cloud Dataflow, Cloud Dataproc, Apache Beam, Apache Spark and Hadoop ecosystem, Cloud Pub/Sub, Apache Kafka)
- Choice of infrastructure
- Distributed systems
- Online (interactive) vs. batch predictions
- Job automation and orchestration (e.g., Cloud Composer)
- Data publishing and visualization (e.g., BigQuery)
- Capacity planning
- Data modeling
- Designing data processing systems
- System availability and fault tolerance
- Designing data pipelines
- Selecting the appropriate storage technologies
- Use of distributed systems
- Schema design
- Mapping storage systems to business requirements
- Architecture options (e.g., message brokers, message queues, middleware, service-oriented architecture, serverless functions)
- Tradeoffs involving latency, throughput, transactions
- Hybrid cloud and edge computing
- At least once, in-order, and exactly once, etc., event processing
Reference: https://cloud.google.com/certification/data-engineer
What is the duration, language, and format of Google Professional Data Engineer Exam
- Format: Multiple choices, multiple answers
- Language: English (U.S.), Japanese, Spanish, and Portuguese
- Cost: $200
- Passing score: 80%
- Number of Questions: 50-60
- Length of Examination: 120 minutes
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