Google Professional-Data-Engineer Exam Syllabus Topics:
| Topic | Details |
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| Topic 1 | - Ingesting and processing the data: The topic discusses planning of the data pipelines, building the pipelines, acquisition and import of data, and deploying and operationalizing the pipelines.
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| Topic 2 | - Designing data processing systems: It delves into designing for security and compliance, reliability and fidelity, flexibility and portability, and data migrations.
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| Topic 3 | - Storing the data: This topic explains how to select storage systems and how to plan using a data warehouse. Additionally, it discusses how to design for a data mesh.
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| Topic 4 | - Preparing and using data for analysis: Questions about data for visualization, data sharing, and assessment of data may appear.
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| Topic 5 | - Maintaining and automating data workloads: It discusses optimizing resources, automation and repeatability design, and organization of workloads as per business requirements. Lastly, the topic explains monitoring and troubleshooting processes and maintaining awareness of failures.
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Reference: https://cloud.google.com/certification/data-engineer
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The Google Professional Data Engineer certification is designed to evaluate the candidates’ skills in designing data processing systems and ensuring solution quality. It is also created to measure their competence in building and operationalizing data processing systems and operationalizing ML models. The potential applicants must complete a single exam to get certified.
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