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Don't wait and enroll in these training courses offered by the official vendor that will help you ace the Professional Data Engineer exam with a good score. Once you take this exam and earn the prestigious Professional Data Engineer certification, you will get a chance to obtain a high-paying job and an amazing opportunity to work with the experts. Don't waste your time on other tasks and start preparing for this exam today. The more you practice the more you will get closer to success as a data analyst or data engineer. Moreover, it will polish your skills throughout and allow you to efficiently in well-reputed companies.
Build & Operationalize Data Processing Systems
- Build & Operationalize Pipeline: This module requires that the learners demonstrate competence in data cleansing, transformation, batch & streaming, data import & acquisition, as well as integration with the new data sources;
- Build & Operationalize Storage Systems: This part will require the students’ skills and competence in the effective usage of managed services, including Cloud Spanner, CLoug Bigtable, BigQuery, Cloud SQL, Cloud Memorystore, Cloud Datastore, and Cloud Storage. It also covers their skills in managing the data lifecycle and storage performance and costs;
- Build & Operationalize Processing Infrastructure: The considerations for this subject area include provisioning resources, adjusting pipeline, monitoring pipeline, and testing & quality control.
Ensuring Solution Quality
The last section of the certification exam evaluates the ability of the learners to design for security & compliance, including identity & access management, legal compliance, data security, and privacy ensuring. Moreover, they should be able to ensure flexibility & portability, reliability & fidelity, as well as scalability & efficiency.
Reference: https://cloud.google.com/certification/data-engineer
Google Professional-Data-Engineer日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Preparing and using data for analysis (~15% of the exam) | 15% | - Sharing data securely
|
| Ingesting and processing the data (~20% of the exam) | 20% | - Performing security considerations
|
| Storing the data (~20% of the exam) | 20% | - Selecting storage systems
|
| Designing data processing systems (~30% of the exam) | 30% | - Designing data processing resources
|
| Maintaining and automating data workloads (~15% of the exam) | 15% | - Automating data processes
|
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