Open Source Analytics

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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Technology today is a weird scene.

Even though IT is usually one of the most important departments (strategically) in an organization, the transparency and accountability is sorely lacking. Have you ever wondered why IT departments are still run as a Cost Center in a world where far more intangible things are easily priced? It’s definitely not because you cannot price IT services. Just that life would become a little tougher for the pseudo-technologists if accountability was brought into IT. I still remember the stares I got when I naively suggested a few years back that we could increase productivity by considering our department (IT) as a Profit Center through notional pricing of services for internal customers. That would have exposed the con, and the idea was immediately killed.

And it is painfully mind-numbing to operate in such a group. And yet, it is the fundamental responsibility of every technologist to comprehend the important function he/she plays and to know what it takes to do his/her job well.

This is something that has bothered me for years now. Right until I came across this blog post just two days back that was putting down in words the same thing many a technologist have always believed in…

The only point of IT is to improve physical operations by providing efficiencies and reducing logical operations by providing automation…
The best business solution is not always the best technology solution. The burden is on you, the technologist, to make the best system the business will use.

I find myself getting strangely addicted to this new-born blog (just 10 days old) because of the absolute clarity of thought, and the raw manner in which it is delivered.

I shall not attempt to explain the post for fear of diluting it. To understand and appreciate for yourself the manifesto that a technologist should live and operate by, please go ahead and read
Things Everyone in IT Should Know…or, The Technologist Manifesto

I’ll be happy if it strikes a chord and rings a bell. And it might be a good idea to drop a comment for dratz (the blogger) if you find yourself nodding your head in agreement.

“I am a bootstrapper. I have initiative and insight and guts, but not much money. I will succeed because my efforts
and my focus will defeat bigger and better-funded competitors. I am fearless. I keep my focus on growing the business—
not on politics, career advancement, or other wasteful distractions.” — Seth Godin’s The Bootstrapper’s Bible.

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Decision trees are one of the most widely used and practical forms of machine learning and data mining. They have been widely researched and applied to a large variety of data mining problems. (Decision trees are also known as Classification Trees or Regression Trees based on whether the classification is being done on real values or on categorical variables.)

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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.