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Google Cloud Big Data & Machine Learning Fundamentals course

This course is a gateway to introduce you to Google Cloud's big data and different machine learning functions. However, to successfully pass this training, you have to attain one year of experience in SQL, extract transform, data modeling, machine learning, programming in Python, and load activities. So, the objectives of the course are the following:

• Recognize the purpose of the key Big data and Machine Learning products in Google Cloud
• Create ML models using BigQuery ML, APIs, and AutoML.
• Hire BigQuery and Cloud SQL for interactive data analysis
• Utilize Cloud SQL & Dataproc to migrate existing MySQL, Pig, Spark, or Hive workloads to Google Cloud

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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

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

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

The following will be discussed here:

• Distributed systems
• Choice of infrastructure
• At least once, in-order, and exactly once, etc., event processing
• Use of distributed systems
• Capacity planning
• Mapping storage systems to business requirements
• Job automation and orchestration (e.g., Cloud Composer)
• Hybrid cloud and edge computing
• Batch and streaming data (e.g., Cloud Dataflow, Cloud Dataproc, Apache Beam, Apache Spark and Hadoop ecosystem, Cloud Pub/Sub, Apache Kafka)
• Selecting the appropriate storage technologies
• Tradeoffs involving latency, throughput, transactions
• Designing data processing systems
• Online (interactive) vs. batch predictions
• Data publishing and visualization (e.g., BigQuery)
• System availability and fault tolerance
• Designing data pipelines
• Data modeling
• Schema design
• Architecture options (e.g., message brokers, message queues, middleware, service-oriented architecture, serverless functions)

Exam Details

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

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