Building & Operationalizing Data Processing Systems
Within this subject area, the test takers should show that they know how to build and operationalize storage systems. Specifically, they need to be conversant with effective use of managed services (such as Cloud Bigtable, Cloud SQL, Cloud Spanner, BigQuery, Cloud Storage, Cloud Memorystore, Cloud Datastore), storage costs & performance, and lifecycle management of data. The students should also be capable of building as well as operationalizing pipelines, including such technical tasks as data cleansing, transformation, batch & streaming, data acquisition & import, and integrating with new data sources. Apart from that, the candidates need to have sufficient competency to build and operationalize the processing infrastructure. This includes a good comprehension of provisioning resources, adjusting pipelines, monitoring pipelines, as well as testing & quality control.
Professional Data Engineer Exam Details
Like other Google exams, this exam also consists of multiple choice and multiple select questions. Consider the fact that you need to pay $200 for the registration. After that, you will access the test for 2 hours which is presented either in English or Japanese. Moreover, you can either take the exam online or have to find a test center near your place to take this test.
There is no formal prerequisite for the exam but it is recommended to have 3-4 years of experience within the data engineering field and to be responsible for the tasks related to data engineering and machine learning. So, on the final test day, you need to have exhaustive knowledge about these domains to perform your best.
- Providing solution quality
- Operationalizing machine learning models
- Designing data processing systems
- Building data processing systems
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Difficulty in Attempting Google Professional Data Engineer Exam Certification
If the user has successfully passed the professional-data-engineer practice exam and has been through professional-data-engineer exam dumps then the certification exam will not be too much difficult as the user has shown aptitude for understanding complicated processes.
Reference: https://cloud.google.com/certification/data-engineer
Google Professional-Data-Engineer日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Ensuring solution quality | 28% | - Reliability and performance
|
| Operationalizing machine learning models | 26% | - Model deployment and monitoring
|
| Designing data processing systems | 22% | - Batch and streaming data processing design
|
| Building and operationalizing data processing systems | 24% | - Data processing and transformation
|






