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.

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Understanding functional and technical aspects of Google Professional Data Engineer Exam Building and operationalizing data processing systems

The following will be discussed here:

• Effective use of managed services (Cloud Bigtable, Cloud Spanner, Cloud SQL, BigQuery, Cloud Storage, Cloud Datastore, Cloud Memorystore)
• Transformation
• Testing and quality control
• Validating a migration
• Building and operationalizing processing infrastructure
• Batch and streaming
• Data acquisition and import
• Adjusting pipelines
• Awareness of current state and how to migrate a design to a future state
• Migrating from on-premises to cloud (Data Transfer Service, Transfer Appliance, Cloud Networking)
• Building and operationalizing storage systems
• Provisioning resources
• Building and operationalizing pipelines
• Monitoring pipelines
• Lifecycle management of data
• Building and operationalizing data processing systems
• Integrating with new data sources
• Data cleansing
• Storage costs and performance

Reference: https://cloud.google.com/certification/data-engineer

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.

• Building data processing systems
• Providing solution quality
• Operationalizing machine learning models
• Designing data processing systems

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Google Professional-Data-Engineer Exam Syllabus Topics: