help a layman understand multi-dimensional data modelling
December 26, 2007 12:02 PM   Subscribe

I'd like to know how multi-dimensional data modelling works.

My company has Cognos BI and I am working closely with the developers. I would like to understand how a star schema works, fact and dimension tables, etc. I'd like to be able to more clearly envision whats going on with the data. How is it different from relational databases? Can you recommend a book or some online articles written for the layman?

I don't necessarily need to understand how *to* model the data, just how to understand data retrieval *from* a model.
posted by goethean to Computers & Internet (2 answers total) 3 users marked this as a favorite
 
Wikipedia has pages on the star schema, fact tables, and
dimension tables. And a category on data warehousing. The star schema page indicates that it is the method by which relational data is viewed as multidimensional data.
posted by beerbajay at 12:50 PM on December 26, 2007


Here's a tutorial form Essential Strategies, which compares common data models to multidimensional equivalents. It can be though of as a streamlining process:while hierarchical model can be thought of as a linear grouping (as in the case of a network tree), a multidimensional system can focus on a variety of factors, such as unfinished tasks, or search strings. Multidimensional systems are often expected to draw data from more than one data source, so they employ flowcharts that focus on variables (tasks, planned budgets, trouble tickets), in addition to particulars (clients, active devices, user privileges). Non-IT staff can trace details in a model from their department's perspective, without delay or confusion.

Another benefit is that a multidimensional model can function like a collaborative project (as with a wiki) or serve as a type of content-management service. It depends on how the criteria are defined, and how the data is distributed (database, indexed directory,etc.).
posted by Smart Dalek at 1:18 PM on December 26, 2007


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