Python programming language is general purpose open source programming language. One of its main features is flexibility and ease of use. Python has a variety of useful set of utilities and libraries for data processing and analytical tasks. Currently due to the rise in demand of big data processing python has grown in popularity because its features are easy to use which are core to the processing of huge chunks of information.

Guido Van Rossum, the pioneer of python, introduced python in the year 1980 and then implemented it in 1989. The intention behind the development of python was to make it open source language that can also be used for commercial projects. The fundamental principle of python is to write the code that is easy to use, highly readable and embrace writing fewer lines of code for achieving a particular task. One of the most popular standard libraries which have ready to use tools for performing a various work is Python Package Index. It was introduced in January 2016 and contains more than 72,000 packages for third-party software usage.

Python plays a critical role in linking data to customers. Recently python has found few entry barriers and many people have had access to have experienced the power of python in the past. So, what makes python the best language for big data analytics?

One of the reasons to choose python is that python ecosystem is very vibrant, the ratings at Redmonk are a proof of the strength python community. The Redmonk ranking is based on StackOverflow discussions and contribution made in Github to determine the popularity of programming language on the method used by users to ask questions about Python and the number of the open source projects contributions.

When making a strategic cloud decision, organizations can follow either one of two ideologies: open or closed.

In the past, major software technologies have been widely accepted because an emerging market leader simplified the initial adoption.  After a technology comes of age, the industry spawns open alternatives that provide choice and flexibility, and the result is an open alternative that quickly gains traction and most often outstrips the capabilities of its proprietary predecessor.

After an organization invests significantly in a technology, the complexity and effort required steering a given workload onto a new system or platform is, in most cases, significant. Switching outlays, shifting to updated or new software/hardware platforms, and the accompanying risks may lead to the ubiquitousness of large, monolithic and complex ERP systems – reason not being that they offer the best value for an organization, but rather because shifting to anything else is simply – unthinkable.

There’s no denying that these are critical considerations today since a substantial number of organizations are making their first jump into the cloud and making preparations for the upsetting shift in how IT is delivered to both internal and external clientele. Early adopters are aware of the fact that the innovation brought about by open technologies can bring dramatic change, and hence are realizing how crucial it is to be able to chart their own destiny.

Sage wisdom states that there are two sides to every coin. This timeless wisdom will be borne out in spades with Windows 8/RT. Let's get into the dark side first.

If your users are veterans of Windows it is safe bet they are going to take one look at Windows 8 and scream blasphemy. Users whose brains are geared towards visual learning will undoubtedly yell the loudest and longest.

There's a good reason for this. Mick Jagger brought his band to the Redmond campus, performing live "Start Me Up" in the summer of 1995 (it was a great show). This heralded in the abandonment of program icons sitting on the desktop and introduced the now legacy Start button.

Ending the life of the 17-year-old start button is not going to go well with some users.

The python keyword global is used in a function to distinguish a local representation of a variable with the same name. 

glbvar = 0

def setglbvar():
    global glbvar # include this declaration so that updates to glbvar are NOT LOCAL to this function
    glbvar = 1

def printglbvar():
    print glbvar     # No need for global declaration to read value of globvar

setglbvar()
printglbvar()       # Prints 1