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.

The iconic software company that is based in King County Washington has been getting almost universally slammed from it's recent Los Angeles press announcement about its entry into the hardware business with the convertible laptop/tablet known as Surface.

Certainly I can see the point that it is now competing with its hardware vendors/partners. Intel has done a good job in the arena creating 'reference designs' without competing with its partners.

There is another viewpoint which seems to be ignored. The cold facts are Microsoft is a public company. This puts Microsoft in a legal position of doing the most it can to return value to its shareholders. Failure to do so means somebody is going to jail.

Microsoft has a vision, which at the end of the day is, a certain way to get enough people to see enough value to hand over their money, to fulfill their fiduciary duty.

The earning potential of a software developer largely depends on their knowledge, their chosen area of expertise, experience and flexibility to relocate if necessary.  In the ever changing landscape of Information Technology, many argue that the way to make more money is to specialize in a technology that fewer people are using.  As an example, there are tons of Java programmers out there, but nowhere near enough in lesser known languages such as Perl or Python.  However, there are plenty of opportunities for folks who are willing to burn the midnight oil to gain skills in these niche disciplines.

Because the Information Technology Industry is a rapidly evolving entity, gunning for the "Next Big Thing" is constantly an arm’s length away.  For this reason, developers looking to get requisite knowledge to successfully compete can, for the most part, expect to resign their weekends for the LOVE of code and studying.   And, it’s fair to say that a stick-to-itiveness to teach yourself how to code can be more important than any degree when job prospecting.  Sam Nichols, a mobile developer at SmugMug, puts it this way: “Build a table, build a computer, build a water gun, build a beer bong, build things that will take a week and build things that need to be done in 40 minutes before the party. Making stuff is what this field is all about and getting experience building things, especially with others, especially when it breaks and fails along the way can help with perspective and resiliency.”

Software developers already skilled at writing code are readily able to translate that knowledge to web development. The fact that the information technology sector has shifted largely to web-based infrastructure and software application as system (SaaS) database and operating system capabilities, means that software developers have a wide variety of opportunity in the web development segment of the consulting and job market.

If you are a software developer seeking to increase your earning potential, gaining expertise in  Web development  enhances your ability to attract new opportunities. The more creative a software developer, the far better chance they will have at benefitting from current market demand for new technologies and software innovation. Customization is hot right now, and software developers involved in the creation of updates and unique features to SaaS can add extra value to their portfolio with very little time and effort involved.

 In order for software developers to stay abreast of their field, continuing education and is required to ensure that technical skills are up-to-date. Gaining knowledge in design of computer applications is one of the main objectives in the development and planning of software products.
Once adequate knowledge has been acquired, many software developers can use those insights to develop custom software for a client as a consultant.

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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