In May 2012 Google Chrome hit a milestone. It kicked Microsoft's Internet Explorer into excess phone oh that oh that second place as the most used browser on planet Earth.
With Microsoft being in second place, it makes a dark hole for Firefox coming in at number three. Google likes to trumpet three key reasons: security, simplicity and speed.
Available for free on Android, Linux, Mac, and Windows. It gets its speed from the open source JavaScript engine written in C++ known as V8.
In my daily use I use Microsoft's Internet Explorer version 10, Apple's Safari (on OS X) and chrome on both Windows 8 and OS X.

Admittedly people do not know anything about Internet Explorer version 10 since you can only get it on Windows 8/RT.

I do not need a crystal ball to know that the Mother of All Browser Battles is set to begin in the fall of 2012 and beyond.

I have said this before and I'm going to say it again.

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.

Communication is one of the main objectives that an organization needs to have in place to stay efficient and productive. A breakdown in accurate and efficient communication between departments at any point in the organization can result in conflict or loss of business.  Sadly, the efficiency between different departments in an organization becomes most evident when communication breaks down. As an example, David Grossman reported in “The Cost of Poor Communications” that a survey of 400 companies with 100,000 employees each cited an average loss per company of $62.4 million per year because of inadequate communication to and between employees.

With the dawning of the big-data era and the global competition that Machine Learning algorithms has sparked, it’s more vital than ever for companies of all sizes to prioritize departmental communication mishaps. Perhaps, today, as a result of the many emerging markets, the most essential of these connections are between IT and the business units. CMO’s and CIO’s are becoming natural partners in the sense that CMO’s, in order to capture revenue opportunities, are expected to master not just the art of strategy and creativity but also the science of analytics. The CIO, on the other hand, is accountable for using technical groundwork to enable and accelerate revenue growth. Since business and technology people speak very different languages, there’s a need on both sides to start sharing the vocabulary or understanding of what is expected in order to avoid gridlock.

In the McKinsey article, Getting the CMO and CIO to work as partners, the author speaks to five prerequisite steps that the CMO and the CIO can take in order to be successful in their new roles.

--- Be clear on decision governance
Teams should define when decisions are needed, what must be decided, and who is responsible for making them.

This section of our beginning python training class always stumps students.  Firstly, because they need to know the difference between a function and a method.  Secondly, they need to understand object oriented programming concepts.  Thirdly, they need to realize that python has three types of methods.  Then they need to know how to use each method, which means they need to know the purpose of each method type.  Then they have to understand mutable versus non-mutable types.  The list goes on.  As part of our python tutorial, I hope to shed some light on this confusing topic.

To begin, the difference between a function and a method in python is that a method is defined within a class.  Here is an illustration:

#function

	def greeting():
	                print "Hello, I hope you're having a great day!"

	class HSGPrinter(object):
	                #method
	                def greeting(self): 
	                                print "Hello, I hope you're having a great day!"

As should be obvious, the second definition of greeting is encapsulated within the HSGPrinter class and is , therefore, refered to as a method.

The astute reader will notice that the greeting method contains one parameter named self.  For those who know C++ , Java or C#, self is equivalent to this i.e. it is a reference to the invoking object: