Re: Another view on analysis and ER
Date: Wed, 05 Dec 2007 03:46:47 GMT
"JOG" <jog_at_cs.nott.ac.uk> wrote in message
> On Dec 4, 8:33 pm, "David Cressey" <cresse..._at_verizon.net> wrote:
> > "JOG" <j..._at_cs.nott.ac.uk> wrote in message
> > news:58c47eeb-adf0-414a-a1f4-9077039bd7fd_at_l1g2000hsa.googlegroups.com...
> > > Genuine question guys. From an E/R perspective (one of the good
> > > variants, that allows relationships to have attributes), if I'm faced
> > > with the following data.
> > > -- Fred married Wilma in Bedrock.
> > > -- Barney and Betty married in Paris.
> > > How do I decide whether I am dealing with a marriage entity or a
> > > marriage relationship?
> > > The literature I'm reading here is telling me that the choice is based
> > > on what 'things' are key to the business. If my business is concerned
> > > with people (tax collection say), 'marriage' is best modelled as a
> > > relationship, whereas if the marriages themselves are my focus
> > > (perhaps I run a church) then its probably better as an entity.
> > > Have I made the right interpretation here, and is there general
> > > agreement here? I am much more comfortable seeing that some variants
> > > allow relationships to themselves have attributes, and that there is
> > > nothing sacred about choices between using relationships or entities,
> > > making it a design decision instead.
> > > Thanks in advance, J.
> > My answer is that it's subjective. If the subject matter experts all
> > a marriage as a relationship, follow their lead. If the subject matter
> > experts all treat it as an entity, follow their lead, but insist that
> > there's a key attroubt that identifies it. (Do the SME's have any such
> > thing as a "marriage ID" attribute?
> > Once you switch over from analysis to design, here's what happens: the
> > attributes that you discovered during analyisis and attached to entities
> > relationships will be carried over from your ER model your design model,
> > which I presume will be a relational model.
> > The entities and relationships themselves, as such, will all disappear!
> > Another thing that will carry over is the keys, used to identify
> > of entities in the subject matter (or UoD if you prefer). Sometimes
> > keys used by the SME (subject matter experts) are a little too informal
> > require "common sense" to disambiguate. That's a special case, and
> > affect this discussion.
> > I'm used to expressing a relational model in terms of tables
> > tables), but I presume that what follows could be transliterated into
> > of relvars without any difficulty.
> > Each entity will have a table of its own, with the attributes that
> > to that entity. The primary key of the table will be the key attribute
> > the entity.
> > Each relationship will have a table of its own, except for a few that
> > be piggy backed onto entity tables. The primary key of a relational
> > will consists of two or more foreign keys, compound. These tables will
> > automatically be normalized up to 3NF unless your analysis put an
> > on the "wrong entity". I'm not sure about normalization beyond 3NF.
> > The above process is so automatic that you can have software that does
> > for you. Indeed, that's what several tools do. They express an ER
> > in terms of metadata, and likewise express the relational model in
> > metadata. And they have a programmed process that will create a
> > model from an ER model. The only tool I know calls the relaional model
> > "physical model" and makes it specific to some product like Oracle or
> > etc. But that's a trivial detail. The software also turns models into
> > diagrams and/or create scripts for you.
> > So where did the entities and relationships go? They disappeared into
> > ether! However,
> > when the application people get around to designing screens and reports,
> > they can tie each feature back to an original entity or relationship.
> > can make the resulting system coherent for the users.
> Ok so one might summarize the following steps:
> 1) initial analysis of business processes and important concepts.
> 2) Formulation of an initial conceptual model (that is necessarily
> slanted to a certain viewpoint of the UoD).
> 3) Translation into a nicely normalized logical model, that's query
> 4) On demand, extract data back out from the neutral logical model,
> shaping it either the original conceptual view, or other conceptual
> views as needs arise from new applications.
Excellent summary. I'd just add one more piece, that's really part of step 1.
1b) Discovery of the data.
> Great. This all makes perfect sense, and is very clear to boot. A
> simple process for creating a thorough yet flexible system. It seems
> obvious even, right?
> So why on earth would /anyone/ want to drop step 3? I'm at a loss as
> to why certain cdt'ers (who are clearly intelligent people) seem to be
> advocating this. An absolute loss I tell you.
> > I apologize for this repsonse. It's really a lot more than you asked
> Yes, how dare you respond with such clarity and thoroughness. Shame on
> > But it's actually easier to use than it is to describe. It may also
> > oversimplify. The relational model that software constructs may not be
> > best relational model that could be designed to deal with the original
> > problem.
Received on Wed Dec 05 2007 - 04:46:47 CET