In this third episode about data integrity, I talk about how to save your data such that computers have an easier time working with it (e.g. for filters), how to ensure that data stays valid by your own rules as you add increasing numbers of validations over the years, about avoiding the mistake of duplicating data across tables and needing to sync these records, about using database transactions to ensure that state changes to multiple rows either all occur or all fail as a unit (preventing invalid intermediate states from cropping up), and lastly about using cascades to ensure the deletion of associated records that should not exist when their 'parent' records are deleted.
Our screencasts are aimed at intermediate and advanced programmers and focus on:
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