The interpreted programming language Python has surged in popularity in recent years. Long beloved by system administrators and others who had good use for the way it made routine tasks easy to automate, it has gained traction in other sectors as well. In particular, it has become one of the most-used tools in the discipline of numerical computing and analysis. Being put to use for such heavy lifting has endowed the language with a great selection of powerful libraries and other tools that make it even more flexible. One upshot of this development has been that sophisticated business analysts have also come to see the language as a valuable tool for those own data analysis needs.

Greatly appreciated for its simplicity and elegance of syntax, Python makes an excellent first programming language for previously non-technical people. Many business analysts, in fact, have had success growing their skill sets in this way thanks to the language's tractability. Long beloved by specialized data scientists, the iPython interactive computing environment has also attracted great attention within the business analyst’s community. Its instant feedback and visualization options have made it easy for many analysts to become skilled Python programmers while doing valuable work along the way.

Using iPython and appropriate notebooks for it, for example, business analysts can easily make interactive use of such tools as cohort analysis and pivot tables. iPython makes it easy to benefit from real-time, interactive researches which produce immediately visible results, including charts and graphs suitable for use in other contexts. Through becoming familiar with this powerful interactive application, business analysts are also exposing themselves in a natural and productive way to the Python programming language itself.

Gaining proficiency with this language opens up further possibilities. While interactive analytic techniques are of great use to many business analysts, being able to create fully functioning, independent programs is of similar value. Becoming comfortable with Python allows analysts to tackle and plumb even larger data sets than would be possible through an interactive approach, as results can be allowed to accumulate over hours and days of processing time.

This ability can sometime allow business analysts to address the so-called "Big Data" questions that can otherwise seem the sole province of specialized data scientists. More important than this higher level of independence, perhaps, is the fact that this increased facility with data analysis and handling allows analysts to communicate more effectively with such stakeholders. Through learning a programming language which allows them to begin making independent inroads into such areas, business analysts gain a better perspective on these specialized domains, and this allows them to function as even more effective intermediaries.

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Who Are the Main Players in Big Data?

The short answer is, yes and no. It depends upon who you are. The purpose of this entry is to help you determine, yes or no.

Full disclosure. This entry is created on a Mac mini. And doing so on Windows 8 (Release Preview). If you are a developer, in my humble opinion you need to test on all platforms you expect your app to run or you are not much of a developer.

To be successful you need to leave politics in geographical territory known as Washington DC. My definition of that is: 14 mi.² of real estate surrounded by reality.

Only in politics can we afford to take sides. Those of us in IT, especially developers need to do our best to be all things to all people. Certainly this is a technical impossibility. However in our game we can get some points for at least being serviceable if not outstanding.

Globalization
Globalization is the fundamental force changing IT service delivery and business's competitive activities in almost every vertical market — and thus economies — in some way, shape or form. One might say that globalization is not a new trend and has been commonplace for quite some time now. Yes, but with the changing economic environment globalizations has special implications for the IT outsourcing industry. With developed countries like the U.S. keeping a strict eye on generating local jobs, IT outsourcing especially in Asian countries such as India and China is expected to see globalization brining in big shifts in business strategy

Potential Impact of Globalization

·         Increase in near shoring in addition to outsourcing. Near shoring essentially refers to existing IT companies setting up development/delivery centers in Nordic and South American regions in order to offer same time zone services and also bypass the laws governing local hiring

·         A truly global delivery model. Service delivery models will have to become more efficient and flexible and work well even if service teams spread across continents

This will mean that large IT outsourcing companies such as TCS will have to expand their presence globally from just having sales offices to actual delivery teams shipping out solutions.

Businesses “Going Green” is so commonplace now it’s more than just an encouraging a trend; it’s become expected of companies big and small. In fact, consumers frequently place more of an obligation on companies to go green than they do themselves. The last few years—the infancy of what may turn out to be a green revolution—have really proven that there are many ways to go green, and that some of these ways are much more financially sound than others. But rather than providing a cut and dry list of green options and their pros and cons, I’d like to take a look at the bigger picture incentives for businesses going green and how consumers are responding.

What does it mean to be green?