Companies have been collecting and analyzing data forever, pretty much.” So what’s really new here? What’s driving the data-analytics revolution and what does it mean for those that choose to postpone or ignore the pivotal role big-data is currently having on productivity and competition globally?

General Electric chairman and CEO Jeff Immelt explains it best when stating that “industrial companies are now in the information business—whether they like it or not.”  Likewise, digital data is now everywhere, it’s in every industry, in every economy, in every organization and according to the McKinsey Global Institute (MGI), this topic might once have concerned only a few data geeks, but big data is now relevant for leaders across every sector as well as consumers of products and services.

In light of the new data-driven global landscape and rapid technological advances, the question for senior leaders in companies now is how to integrate new capabilities into their operations and strategies—and position themselves globally where analytics can influence entire industries. An interesting discussion with six of theses senior leaders is covered in MGI’s article, “How companies are using big data and analytics,” providing us with a glimpse into a real-time decision making processes.

No matter what type of business you’re in, boosting your bottom line is always in the back of your mind. In a rough economy, it can be tempting to focus too much on pulling in more money and not enough on containing it from within.

That’s right, containing it. You have the potential to lose hundreds of thousands of dollars every year right under your nose from something as simple as lack of or ineffective computer training.

How much do the employees you have working for you right now really understand about technology? How good is your IT tech department? Technology changes faster than a blink of an eye and oftentimes, businesses struggle to keep their top employees trained.

With millions of dollars being lost to Internet espionage, file corruption and other computer crimes, staying on top of changes is essential. Recently, online learning centers have been emerging as the go-to method for quick and inexpensive learning. Unfortunately, this type of computer learning isn’t always the best solution.

I suspect that many of you are familiar with the term "hard coding a value" whereby the age of an individual or their location is written into the condition (or action) of a business rule (in this case) as shown below:

if customer.age > 21 and customer.city == 'denver'

then ...

Such coding practices are perfectly expectable provided that the conditional values, age and city, never change. They become entirely unacceptable if a need for different values could be anticipated. A classic example of where this practice occurred that caused considerable heartache in the IT industry was the Y2K issue where dates were updated using only the last 2 digits of a four digit number because the first 2 digits were hard-coded to 19 i.e. 1998, 1999. All was well provided that the date did not advance to a time beyond the 1900’s since no one could be certain of what would happen when the millennia arrived (2000). A considerably amount of work (albeit boring) and money, approximately $200 billion, went into revising systems by way of software rewrites and computer chip replacements in order to thwart any detrimental outcomes. It is obvious how a simple change or an assumption can have sweeping consequences.

You may wonder what Y2K has to do with Business Rule Management Systems (BRMS). Well, what if we considered rules themselves to be hard-coded. If we were to write 100s of rules in Java, .NET or whatever language that only worked for a given scenario or assumption, would that not constitute hard-coded logic? By hard-coded, we obviously mean compiled. For example, if a credit card company has a variety of bonus campaigns, each with their own unique list of rules that may change within a week’s time, what would be the most effective way of writing software to deal with these responsibilities?

Jeff Nelson, a former Googler and inventor of Chromebook says on Quora, “One habit I've clung to is writing small prototypes when I'm trying to learn new concepts.
For example, I'll sit down with a book or a web page, and over the course of a few hours, write 30 or 40 programs all of them only a few dozen lines long.  Each program intended to demonstrate some simple concept. This prototyping makes it very easy to try out many concepts in a short period of time.”

Miguel Paraz, Software Engineering Student habit is to “keep a log in a text file or document on my work computer. Before trying to solve a problem, I write it down first. And then I describe the details as they happen.”