I'm still partial after all this time to the old school Kimball book, even if I'm not working directly out of the dimensional modeling world as often now.
That said, I'm VERY interested in Fact-Oriented Modeling after seeing Marco Wobben's presentation at EDW. There's a book and also this website to cover it -- http://www.factbasedmodeling.org/.
Eric Schiller[All DATAVERSITY Members] @ Mar 26, 2019 - 07:01 AM (America/Pacific)
I agree Kimball is pretty good but it the book
is quite thick.
There's an EdX course on data modeling which is ok but is a bit slow
I started the new Data Engineering course from Udacity and think it is pretty good. A lot of good hands on examples.
Yeah, I found that the first five or so chapters of Kimball are the really essential stuff, then most of the rest of the book is templates for specific situations until you get to the ETL stuff and a few other things at the end.
That saves a LOT of reading up front so that you can go back and reference later as needed.
Definitely worth looking into other stuff like canonical modeling, and some other more general principles as well to keep up with the agile world.
It's been my experience that form almost always follows function. What I mean by that is that there are commonalities across all healthcare databases (operational and analytic), across supply chain, across service model. So, your basic structures would be the same across all implementations within the same industry (with your own customizations, of course).
For example, there is progress being made to get all of the Blue Cross Blue Shield network participants to use a common storage format, as well as a common communication format, to promote automatic electronic data handling. You might think that dragon would have already been slayed, but it has not - there are a large number of translation/adapter fittings in place to keep the data flowing, with unsophisticated validation and a lot of manual processes. But the more we can work together to share the details, to define that industry standard, the easier it will be to put automated processing rules in place and to increase the overall data quality.
So, depending on your needs, you should review (and maybe experiment) for what works best with your business model - and then decide the best fit for your company.
My favourite books are Len Silverston's Data Model Resource Book series due to the insight into business domains and the patterns provided to rapidly getting a modelling project started. I'm currently working my way through The Nimble Elephant too (John Giles is another data modelling hero).
Graeme Simsion's book also must-reads.
Ralph Kimball's Data Warehouse Tookit is a classic (I couldn't say the same for Building the Data Warehouse though).
The data modeling book I use the most is Chris
Schema: The Complete Reference. I design dimensional
databases a lot and it gives me a great tool to quickly apply the
best design practices to my particular situations. I also like Len
Aaron Fuller, CBIP
Founder & Principal Consultant
Superior Data Strategies
For beginners I recommend "Data Modeling: A Beginner's Guide" by Andy Oppel. For MongoDB I recommend the publicly accessible Mongo Manual online.
I like Data Modeling Made Simple by Steve Hoberman and Data Modeling for the Business by Hoberman, Burbank and Bradley.
I like your choices, Mark. For full-time modelers Simsion's 'Data Modeling Essentials' (get the third edition) is a great job manual for data modeling. Silverston's three-volume compendium has been a very useful lookup reference to me too. Kimball's Toolkit is the warehousing breakthrough classic.
I spent a lot of time on Chris Date's 'Introduction to Database Systems', rigorous but a tough read. William Kent's little book 'Data and Reality' earns every rave it gets. Have a look at these too.
Vladimir Sosiurko, CDMP
Definitely Steve Hoberman is what you can start right from the beginning of your career and get it to the next few levels
I just finished David Hay's new book, *Achieving Buzzword Compliance. *It
gives some good background on Data Architecture and Data Modeling terms and
concepts. It has really helped me fill in some of the gaps in my
understanding of these areas.
Red Hat NC https://www.redhat.com
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On Fri, Jul 19, 2019 at 11:05 AM William McKnight <
[login to unmask email]> wrote:
> I like Data Modeling Made Simple by Steve Hoberman and Data Modeling for
> the Business by Hoberman, Burbank and Bradley.
> -----End Original Message-----
Jose Mari Taleno
Kimball Data Model is still applicable for me. I'm keen on learning Data Vault Modelling however, the investment to start right with it is so high that makes it hard to get support from the business.
Jose, Kimball data marts can source from data vault structures, so it's not a question of Kimball or data vault. Data vault complements Kimball. As far as the investment to start, it doesn't have to be big. The data vault approach is meant to be agile and can be built in iterations. It doesn't have to be a monolithic project like data warehouses we used to build in the old days.