Google Certified Professional Data Engineer Exam (Professional-Data-Engineer日本語版) : Professional-Data-Engineer日本語

Operationalizing Machine Learning Models

Here the candidates need to demonstrate their expertise in using pre-built Machine Learning models as a service, including Machine Learning APIs (for instance, Speech API, Vision API, etc.), customizing Machine Learning APIs (for instance, Auto ML text, AutoML Vision, etc.), conversational experiences (for instance, Dialogflow). The applicants should also have the skills in deploying the Machine Learning pipeline. This involves the ability to ingest relevant data, perform retraining of machine learning models (BigQuery ML, Cloud Machine Learning Engine, Spark ML, Kubeflow), as well as execute continuous evaluation. Additionally, the students should be able to choose the relevant training & serving infrastructure as well as know how to fulfill measuring, monitoring, and troubleshooting of Machine Learning models.

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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:

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

The Professional Data Engineer exam is the industry-standard exam that proves the candidate’s ability to do data-driven decision-making by assembling, transforming, and publishing data. If you are rooting for a career in data engineering, you should take this test. It will lead you to attain the Professional Data Engineer certification issued by Google.

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

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Who should take the Google Professional Data Engineer exam

Individuals should pursue the exam if they want to demonstrate their expertise and ability to design and develop Data Engineering. Following professional get benefited from Google Professional Data Engineer Certification

• Business analysts
• Data analysts
• Developers responsible for managing big data transformation initiatives
• Data architects
• Data scientists
• Data engineers