Open Source Analytics

And here’s an excellent presentation on calculating ROI for BI projects.

BetterManagement.com: Calculating ROI for BI Projects

If you have followed some of the earlier posts, you would remember that a data mart is created as a star schema through a process known as dimensional modeling. In this post we will create a dimensional model for Sales data mart at a hypothetical retailer. (more…)

Here is a link to a CIO Magazine editorial outlining some successful BI implementations. Do note that for BI to be really successful, it has to be made available to a wide range of people within the organization and not just to a privileged few. Widespread information dissemnitation within the organization through adoption of BI is what “Information Democracy” is all about.

Business Intelligence: Not Just for Bosses Anymore – Editorial – CIO

How can management follow medicine’s lead and rely on evidence, not on half-truths?

A good question to ask all those ’seat-of-the-pants’ managers and decision makers: How would you like it if you found that your medical practitioner didn’t look at the evidence and engaged in a similar ‘gut-feel’ decision making in matters concerning your health?
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The OLAP Report is one of the oldest and most authoritative independent research resources for organizations buying and implementing OLAP applications. It was started by Nigel Pendse in October 1994, as an authoritative and independent voice seeking to clear the hype and misinformation flooding the field. (more…)

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.

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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?

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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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.

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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.