Mon 27 Mar 2006
While we may all differ on the definitions of BI, we do know that it is all about extracting and delivering specific and useful information in the midst of the data-explosion around us. And all the definitions and implementations, in their own ways, are geared towards that objective.
Margaret Dunham, the author of Data Mining: Introductory and Advanced Topics once said:
Data mining research and practice is in a state similar to that of databases in the 1960s.
Mon 27 Mar 2006
Read the seven most common flaws in BI Implementations as noted in 2006 Gartner BI Summit: BI’s seven fatal flaws
And here is a 2005 Gartner press release outlining the same common flaws.
Does it ring a bell?
Mon 20 Mar 2006
In this recent article called “The Open Source BI Trend Will Grow - Here’s Why” on the DM Direct Newsletter, Rick Mortensen of MARVELIt explains why open source BI is gaining traction and will continue to grow.
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Tue 14 Mar 2006
There are far too many conflicting and confusing definitions of Data Mart and Data Warehouse floating around. The long running debate between Ralph Kimball and Bill Inmon, the two Titans of Data Warehousing, only adds to the confusion.
In this post, we’ll try to get some sanity around the concepts, without getting drawn (hopefully) into the crossfire.
Fri 10 Mar 2006
A good resource on Data Mining using R environment is “Data Mining - Desktop Survival Guide” by Graham Williams. Its a well researched and frequently updated free online book. Graham does a good job of going through the data mining process and provides detailed descriptions of the commonly used algorithms.
Exmaples are in R (all with R source code, of course), with some good examples of graphical visualization as well.
Click here for Data Mining - Desktop Survival Guide
R Environment is a part of DecisionStudio-Professional and can also be separately downloaded from http://r-project.org.
Tue 7 Mar 2006
I would, in due course, spend some time on the R Environment (available as part of DecisionStudio Professional, and separately downloadable from http://r-project.org). R provides an excellent alternative to commercial products for modeling, statistical analysis, and graphics. Originally designed by AT&T Bell Labs, the R environment is fast becoming the standard for cutting edge number crunching.
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