The document presents strategies for detecting and managing schema drift, which is defined as changes in source or target data definitions that can lead to poor data quality and frustration for data professionals. It discusses coping mechanisms for both source and destination schema drift, emphasizing the importance of designing resilient workflows that can adapt to changes using tools like FME. Additionally, it provides insights into automating workflows through schema validation and introduces various licensing options for FME products.
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