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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.

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

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:

• 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
• Create ML models using BigQuery ML, APIs, and AutoML.
• Recognize the purpose of the key Big data and Machine Learning products in Google Cloud

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