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 importance of variables in any programming language can’t be emphasised enough. Even if you are a novice, the chances are good that you will have been using variables for quite a while now.

They are the cornerstone of any language and without them we would not be able to accomplish much of anything. However, most of you up until this point have probably only been working with standard variables, variables which can hold single values such as an integer, a single character, or a string of text.

In this tutorial we are going to take a look at a more special type of variable called an array. Arrays can seem quite daunting at first glance but once you get used to working with them you will wonder how you ever managed to program without them.

The reason arrays are special is because they can hold more than one value. Think about this: say you create a variable which contains a line of text like the code below:

Many individuals are looking to break into a video game designing career, and it's no surprise. A $9 billion industry, the video game designing business has appeal to gamers and non-gamers alike. High salaries and high rates of job satisfaction are typical in the field.

In order to design video games, however, you need a certain skill set. Computer programming is first on the list. While games are made using almost all languages, the most popular programming language for video games is C++, because of its object-oriented nature and because it compiles to binary. The next most popular languages for games are C and Java, but others such as C# and assembly language are also used. A strong background in math is usually required to learn these languages. Individuals wishing to design games should also have an extensive knowledge of both PCs and Macs.

There are many colleges and universities that offer classes not only in programming but also classes specifically on game design. Some of these schools have alliances with game developing companies, leading to jobs for students upon graduation. Programming video games can be lucrative. The average game designer's salary is $62,500, with $55,000 at the low end and $85,000 at the high end.

Programmers are not the only individuals needed to make a video game, however. There are multiple career paths within the gaming industry, including specialists in audio, design, production, visual arts and business.

Designing a video game can be an long, expensive process. The average budget for a modern multiplatform video game is $18-$28 million, with some high-profile games costing as much as $40 million. Making the game, from conception to sale, can take several months to several years. Some games have taken a notoriously long time to make; for example, 3D Realms' Duke Nukem Forever was announced in April 1997 and did not make it to shelves until July 2011.

Video game programmers have a high level of job satisfaction. In a March 2013 survey conducted by Game Developer magazine, 29 percent of game programmers were very satisfied with their jobs, and 39 percent were somewhat satisfied.

If you're interested in a game development career, now's the time to get moving. Take advantage of the many online resources available regarding these careers and start learning right away.

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.”