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Build Your Data Transformations Faster And Safer With SDF

Data Engineering Podcast

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Understanding Data Integrity Requires Precision

In data management, especially within larger companies, a significant proportion of columns—up to 50%—are often varchars, which can obscure the true nature of the data. This lack of specificity can lead to critical errors, as illustrated by a case where analyst errors arose from treating distinct user IDs as equivalent. Effective data governance necessitates clear categorization, where business logic can enforce constraints, preventing erroneous joins and ensuring data integrity. The implementation of a robust type system that clearly differentiates data entities, such as user IDs from different acquisitions, is vital for maintaining accurate analytics and safeguarding against privacy concerns.

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