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The Importance of a Raw Layer in Data Management
The raw layer is the historical repository of what things look like at different points in time and allow you to rebuild downstream. The data lake design is that you've always got that data. So if you want to change the way you're managing your slowly changing dimensions or one of your dimension tables, so suddenly, you know, previously you never cared about someone's address, but actually you decide to do fraud analytics. And therefore maybe you actually do want to know what their address is. You can do that because you've got the history and be you can kind of spin up the necessary compute to do that in a relatively quick way.