To get a further and more detailed understanding about data modelling, there are plenty of tutorials, books, and presentations about data modelling. Among these, I found the following quite useful.
- Len Silverston (and his team)'s work "the data model resource book" is definitely a "must-have" for all data modellers. The three series of the book is a "make-a-living" tool for many data modellers in the industry.
- The classical book "Data Modelling Essentials" by Graeme Simsion and Graham Witt is another book that I recommend everybody to keep in your book shelf.
- If you are more at the business side and would like to know a bit more about data modelling, I would recommend Steve Hoberman's book "Data Modelling Made Simple."
- As we've been talking about BI and data warehousing in this blog, the typical theory of multidimensional modelling and star-schema and snow-flake is well introduced in Kimball's book series. Here I would recommend the dimensional modelling book in his series.
- Besides these books for industry users, I think there existing many database theory books that use 1 or 2 chapters to talk about E-R modelling, normalization, and dimensional modelling. It is fair enough for university students. And I would actually recommend new-comers to the data modelling world to start your readings from these classical theories. (I've introduced two books in a previous posting.)
- More intellectual work exists as products or services from various companies rather than being described in books or blog notes. The IBM industry data model has been well made for several industries. Similarly, Teradata has its industry data model sold together with its platform. Even SAS has its own data model to support its well-known BI platform. What one needs is to find out an employer who would like to hire you and train you to get the knowledge of these industry products. Right?
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