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An e-commerce enterprise stores petabytes of structured transaction history and customer support text transcripts in BigQuery. The organization wants to improve its existing business logic by adding predictive customer churn models and automated sentiment analysis on support logs.
The engineering team has established SQL expertise but limited experience managing custom machine learning infrastructure or Python-based deployment frameworks. They need a managed solution that avoids extensive data movement and allows them to build tabular predictive models and leverage advanced foundation models for natural language tasks directly.
Which architecture should you recommend?
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