Data Science Model Deployments and Cloud Computing on GCP - Lab - Data Validation Using App Engine

The video tutorial covers using BigQuery to access a public ML dataset for fraud detection. It explains the dataset's structure, including 31 anonymized columns and a class column for fraud detection. The tutorial outlines data validation rules, such as ensuring all columns are present and class values are valid. A Python script is used for validation, and the deployment process on Google App Engine is demonstrated. Future steps involve chaining applications using GCP Workflow.

What is the first step in the use case mentioned in the video?

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What happens if the data validation fails?

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What are the two rules applied during data validation?

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