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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.
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The Google Professional Data Engineer certification exam has the duration of 2 hours. The qualifying test is made up of multiple-select and multiple-choice questions. The exam is available either in Japanese or English. To register for it, you are required to go through the official webpage and pay the fee of $200 plus applicable taxes. While completing the registration process, the potential individuals can choose the preferred method of exam delivery. It can be taken in person at the nearest testing center or online from a remote location.
Reference: https://cloud.google.com/certification/data-engineer
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Designing data processing systems | 22% | - Batch and streaming data processing design
|
| Topic 2: Building and operationalizing data processing systems | 24% | - Data processing and transformation
|
| Topic 3: Operationalizing machine learning models | 26% | - ML pipeline integration
|
| Topic 4: Ensuring solution quality | 28% | - Security and governance
|
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