Introduction

Data engineers are responsible for finding trends in data sets and developing algorithms to help make raw data more useful to the enterprise. This IT role requires a significant set of technical skills, including a deep knowledge of SQL database design and multiple programming languages They collect, transform, and visualize data. The Data Engineer designs, builds, maintains, and troubleshoots data processing systems with a particular emphasis on the security, reliability, fault-tolerance,scalability, fidelity, and efficiency of such systems.

Google Professional-Data-Engineer Certification Exam is a highly prestigious certification program offered by Google for individuals who want to establish themselves as professional data engineers. Google Certified Professional Data Engineer Exam certification validates the skills and knowledge required to design, build, operationalize, secure, and monitor data processing systems. It is designed for individuals who have experience working with data processing systems, data warehousing, and data analysis technologies.

Understanding functional and technical aspects of Google Professional Data Engineer Exam Designing data processing systems

The following will be discussed here:

• Schema design
• Batch and streaming data (e.g., Cloud Dataflow, Cloud Dataproc, Apache Beam, Apache Spark and Hadoop ecosystem, Cloud Pub/Sub, Apache Kafka)
• Online (interactive) vs. batch predictions
• Distributed systems
• Use of distributed systems
• At least once, in-order, and exactly once, etc., event processing
• Data publishing and visualization (e.g., BigQuery)
• Job automation and orchestration (e.g., Cloud Composer)
• Capacity planning
• Mapping storage systems to business requirements
• Selecting the appropriate storage technologies
• Choice of infrastructure
• Hybrid cloud and edge computing
• Architecture options (e.g., message brokers, message queues, middleware, service-oriented architecture, serverless functions)
• System availability and fault tolerance
• Designing data processing systems
• Data modeling
• Tradeoffs involving latency, throughput, transactions
• Designing data pipelines

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Google Professional-Data-Engineer Exam Syllabus Topics:

Reference: https://cloud.google.com/certification/data-engineer

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