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  • Indeed there will be some manual review to do, I don't expect a tool to do it fully automatically. But I'm pretty sure most of the work can be automated by analyzing existing data in the DB (at least, samples of it), and/or fields name/type . Commented Sep 23, 2012 at 12:20
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    How? Normalization is defined on join dependencies and functional dependencies. A functional dependency is basically easily defined as: for every possible value of a superkey, there is exactly one value in the functional dependency. You can't get there by automating the review of the data because just because you have, for your current set, what appears to be a functional dependency, that doesn't mean that a new key will conform. It is very much like the old correlation vs causation division. You can't induce a functional dependency by observing what is currently in the database. Commented Sep 23, 2012 at 13:42
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    at least a tool can suggest that a relation maybe exists. if quality and size of the data sample is large enough the accuracy of such a guess will be high enough for practical purpose. Commented Sep 23, 2012 at 17:03
  • Maybe. But let's take a real example which is pretty hellish relational-design wise: addresses. How should mailing addresses be normalized? How many tables should be suggested? By my understanding of 3NF, you need tables for countries, states/provinces, and cities. I don't know whether postal code/city breakdowns make sense but they probably do. But how do you analyze existing data and determine that (city, state) -> country? How do you determine if/if not postal codes globally relate to these constructs? Commented Sep 24, 2012 at 1:04