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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.
Reference: https://cloud.google.com/certification/data-engineer
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Training Courses Recommended for the Exam Preparation
Training courses are meant to help candidates to learn about the Google exam syllabus and prepare well. It has hands-on labs and expert support that will allow you to get in-depth knowledge of each domain covered in the test. So, these are some of the best training courses offered by Google for the Professional Data Engineer certification exam.
Google Professional-Data-Engineer Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Designing data processing systems | 20% | - Designing for regulatory and security requirements
|
| Topic 2: Operationalizing machine learning models | 20% | - Preparing data for ML
|
| Topic 3: Maintaining and automating data workloads | 18% | - Resource optimization
|
| Topic 4: Building and operationalizing data processing systems | 25% | - Building data pipelines
|
| Topic 5: Ensuring solution quality and reliability | 17% | - Troubleshooting and optimization
|
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