Open Source Analytics

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?

On Friday we released DecisionStudio Professional - a comprehensive and free desktop BI Platform that gives you all the tools needed for analytics under a single package licensed under GNU Public License (GPL).

DecisionStudio Professional (DSP) is an advanced graphical data mining, reporting, modeling, and analysis environment built on top of the best-of-breed open source projects. Some of these include:
— Optimized MySQL database as data warehouse platform
— SQL Workbench (MySQL Query Browser and DBDesigner) for Data Analysts
— R environment for statistical analysis and modeling
— iReport Reporting GUI and JasperReport reporting library
— Python with Boa Constructor IDE for application and GUI development

DecisionStudio Professional is the only end-to-end open source analytics platform that provides comprehensive capabilities to each role. Data Analysts get to store, process, and publish data on a standard MySQL platform; Reporting Analysts would like iReport and the integration with Office tools; and Modelers would love the excellent R Environment. It also includes Python along with a drag-n-drop GUI building environment for analytics Application Developers.

You can find out more about DecisionStudio Professional at decisionstudio.com, and can download your copy at Sourceforge.net. Click here to download the product brochure (PDF).

Go ahead, it’s completely free and will always stay so.

Analytics and Business Intelligence is really about the conversion of raw data into optimal and actionable decisions to create tangible business value. Otherwise, what’s the point?
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Merry Christmas folks. Hope you have been having a great time.
:-)

Prompted by a reader comment, this post is about that elusive difference between Analytics and regular IT. Or is there really a difference?
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Probably because they are creaming the market anyway, consultants from the bigshot analytics and BI companies are a royal pain to work with.

What we want from a million-dollar implementation project is the end result that delivers tangible value. And as that smilling pre-sales guy convinces us to sign that million-dollar contract, this is what we are thinking with a nagging gut feel that something might be amiss:

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In Europe they call it Operations Research (OR). OR is the discipline of applying advanced analytical methods to help make better decisions.

By using techniques such as mathematical modeling to analyze complex situations, operations research gives executives the power to make more effective decisions and build more productive systems based on:

* More complete data
* Consideration of all available options
* Careful predictions of outcomes and estimates of risk
* The latest decision tools and techniques

Read The Executive Guide to OR Research by the Institute for Operations Research and the Management Sciences.

If you found the course on data-mining a little too long or abstract for your taste, here is your Field Guide to Data Mining.

Data mining offers great promise in helping organizations uncover patterns hidden in their data that can be used to predict the behavior of customers, products and processes. However, to realize the value of data-mining, it has to be done by people who understand the business, the data, and the general nature of the analytical methods involved. Unfortunately, due to the amount of hype involved, a surprisingly large number of people mistake the tools for the craft of data mining. (more…)

Unfortunately most of the websites on analytics and data-mining are chock full of hype and have very little content that you can actually learn from. Still, there are some sites that are regularly referred to by the insiders. Very few, but still.

Here is a great Course on Data Mining created by Dr. Piatetsky-Shapiro and 3 computer science faculty members from Connecticut College working in conjunction with an instructional designer.

This course is organized as 19 modules of 75 minutes and provides a thorough overview of the field. The detailed course outline is available here.

If you know of some other good free courses about data-mining/BI/analytics, please let me know and I’ll put them up here.

Data mining has been defined as

The nontrivial extraction of implicit, previously unknown, and potentially useful information from data

and

The science of extracting useful information from large data sets or databases.

Well, in simpler terms, data-mining is what you do when you are unable to know your customers as you would if you were living and working in a small community. (more…)