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?

As someone who works in many facets of the music industry, I used to seethe with a mixture of anger and jealousy when I would hear people in more “traditional” goods-based industries argue in favor of music content-based piracy. They made all the classic talking points, like “I wouldn’t spend money on this artist normally, and maybe if I like it I’ll spend money on them when they come to town” (which never happened), or “artists are rich and I’m poor, they don’t need my money” (rarely the case), or the worst, “if it were fairly priced and worth paying for, I’d buy it” (not true).  I always wondered if they’d have the same attitude if 63% of the things acquired by customers in their industries weren’t actually paid for, as was conservatively estimated as the case for the music industry in 2009 (other estimations put the figure of pirated music at 95%). Well, we may soon see the answer to curiosities like that. Though one can say with tentative confidence that music piracy is on the decline thanks to services like Spotify and Rdio, it could be looming on the horizon for the entire global, physical supply chain. Yes, I’m talking about 3d printers.

Before I get into the heart of this article, let me take a moment to make one thing clear: I think these machines are incredible. It’s damn near inspiring to think of even a few of their potentially world-changing applications: affordable, perfectly fit prosthetic limbs for wounded servicemen and women; the ability to create a piece of machinery on the spot instead of having to wait for a spare to arrive in the mail, or en route if your car or ship breaks down in a far away place; a company based out of Austin, TX even made a fully functioning firearm from a 3d printer a few months ago.

If these machines become as consumer-friendly and idiot-proof as possible (like computers), it’s possible that in a matter of decades (maybe less), a majority of U.S. households will have their own 3d printer. There’s also the possibility they could take the tech-hobbyist path, one that is much less appealing to the masses. Dale Dougherty of Makezine.com estimates there are currently around 100,000 “personal” 3d printers, or those not owned for business or educational purposes. I don’t think they’ll ever be as ubiquitous as computers, but there are plenty of mechanically inclined, crafty hobbyists out there who would love to play around with a 3d printer if it was affordable enough.

That being said, is there reason to worry about the economic implications of consumers making what they want, essentially for free, instead of paying someone else to produce it? Or will the printers instead be used for unique items more so than replicating and ripping off other companies’ merchandise in mass amounts? The number of people working in industries that would be affected by a development like this is far greater than the number of people who work in content-based industries, so any downturn would probably have a much larger economic implications. Certainly, those times are a ways off, but a little foresightedness never hurt anyone!

If you're someone who's interested in computer programming, chances are you've considered pursuing a career in it. However, being a computer programmer is definitely not for everyone, as it takes some special characteristics to succeed as a computer programmer.

Good at Math

While you don't have to be a math genius in order to be a good computer programmer, being good at math really does help. In general, as long as you know your trigonometry and advanced high school algebra, you should be set for programming.

However, in a few instances, knowledge of more advanced math ends up being necessary. For example, for shader programming, you should be familiar with integration of multiple variables, matrix algebra, and basic differentiation. You will also require considerable math skills in order to program 3D.

Excellent Problem Solver

To be a successful computer programmer, you definitely need to be an excellent problem solver. It is vital for a computer programmer to break a problem down into small parts. They must then be able to decide the best way to approach individual pieces of the problem. Computer programmers also need to know how to anticipate and prevent potential problems. While problem-solving, they also need to keep in mind things like user experience and performance.

If you're not a good problem solver, knowing a particular language and syntax will be useless if you can't even identify the problem at hand. Therefore, excellent problem solving skills are a critical foundation for computer programming.

Patience

If you are not a patient person, you will quickly become very frustrated with computer programming. Problem-solving is not always easy and fast. In fact, it may take a very long time, especially if you're either inexperienced or working on an especially hard project.

Debugging after the coding process is also very frustrating and tedious. No matter how hard you try, you will always have bugs in your coding, and these bugs, while often easy to fix, tend to be very difficult to detect. Therefore, you will end up spending a lot of your time searching for bugs that take very little time to fix.

Well-Rounded Skills

Generally, computer programmers who are very skilled in one area tend to stick around longer than jack-of-all-trades, as specialized programmers are harder to replace with outsourcing than general programmers. Therefore, it will do you well to specialize in one area of computer programming.

However, while specializing is good, you should still know at least a little about everything, especially skills that relate to the area you specialize in. For example, if you're a core Java programmer, you should know about SQL programming and ideally a scripting language or some regular expressions.

As you can see, not everyone has what it takes to pursue computer programming as a career and succeed at it. In fact, just because you love to program doesn't mean it's a good career choice for you. However, if you feel that you possess all the characteristics listed above, then you should definitely consider computer programming as a career.