Re: Time for my yearly question:

Tech-Archive recommends: Repair Windows Errors & Optimize Windows Performance

From: frank20 (frank20_at_cox.net)
Date: 07/16/04 

Date: Fri, 16 Jul 2004 10:50:04 -0500

"Ian Boyd" <admin@SWIFTPA.NET> wrote:
> Where is a good introduction to what a warehouse is?

One (slightly oversimplified) way to understand / think about the topic is
to start by considering a 'real world' warehouse...say one for a very large
distributer of goods for dozens of types of retail stores.

While the 'warehouse' contains everything that ends up in stores for sale,
it, itself, is not a store. All the selling, product display, etc, goes on
at the stores. For the stores to function / make money, it is critical that
the distributer be able to offer / deliver the products asked for, when
needed. This means that the warehouse and the store(s) are separate, but
inter-dependent.

The distributer has a constant need to monitor / analyze / act what is going
in the warehouse, among the suppliers to the warehouse, and, of course, the
stores 'pulling' products from his warehouse. What distributer is looking at
/ for is different than, say, what the owners / operators of the stores are
looking at.

Using a very simple example, if the distributer stocks 'TVs', what matters
is how many, of what kind, from whom, are currently in stock...and, most
importantly...how many should be there in a week or a month. All of this
'interest' is at an 'aggregate' level...meaning, it probably does not really
matter to the distributer which store chains, or stores within a chain, sell
the TVs...only 'overall' how many TVs are moving through the warehouse.

Clearly, to do this kind of monitoring / analysis (and other warehouse
management functions), only certain kinds of information is necessary. I am
not going to enumerate the entire typical set, but only point out that it
falls into three very general categories: numbers, descriptions, and dates.
Translated to 'warehouse-ese', I would call these components become
facts/metrics, attributes, and, well, 'dates'. (I personally like to keep
the notion of dates as separate for a practical reason...in SQL server, for
example, numbers have a collection of assigned / available datatypes, so do
descriptions (text), and so do dates).

Back to the 'real world' example. What is mainly going on in a 'store' (if
it is successful) is sales transactions...and the system(s) supporting it
are analagous to the OLTP systems. What is going on in the warehouse, at
some level, is analysis (of inventory turn-over, of supply lead times, of
feedback from the stores, etc.)...and the system(s) supporting it are
analagous to BI systems.

For the BI systems to work, they need a database and flow of info from the
physical warehouse, from suppliers, and from the stores. In terms of the
database, it needs to be organized to support its purpose...which is, as
noted, analysis rather than transaction processing. This generally means
factoring how analysis is done (by 'attributes' and 'dates') into tables /
relationships...with each needed 'how' ending up as a dimension within the
database. Building a 'date dimension' into the datbase simply means that,
since 'date' is often part of an analysis query, the database design
facilitates that use (through tables / relationships, indices, etc).

While realizing that this is a gross simplification, I hope that it helped
to answer your question...or, at least, provided a way for you to think
about it more concretely.

Regards,
Frank J. Hannaford

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