For those newly moving into the realm of programming, the important question to mull over is what programming language or technology to specialize in. On the other hand, those who are already working as a software developer, the constant worry remains whether their current technology would become obsolete very soon.

Both these concerns could be easily addressed by checking the list of programming languages that are highly in demand and formulating the career by modifying your specialization accordingly. The supply for the developers have not met with the demand in these programming languages yet, making them most viable options for career.

Popular Programming Languages Based on TIOBE Index

The top 10 list of programming languages which are highly in demand in 2014 is listed below in the order of popularity. These languages are identified from the TIOBE Programming Community index which consists of 20 top programming languages. TIOBE index is an indicator of the popularity of programming languages and is updated once in every month.  This index is calculated using multiple search engines, and the ratings are based on the number of skilled engineers world-wide, courses and third party vendors.

With the skyrocketing popularity of Android and iOS operating systems, software developers got a whole new arena opened up. Many of the programmers have progressed to concentrate solely onto Mobile Technology Development. This is mainly due to the high demand as well as numerous lucrative ideas left to explore in the Mobile App world.

Exponential growth of smartphone users

As per the survey by eMarketer, the number of smartphone users across the globe crossed 1 billion almost two years ago. The expected number of smartphone users by 2014 end is 1.75 billion.

With smartphones, iPads and Tablets getting more accessible and less expensive day by day, the development potential for mobile apps is truly vast. The under-penetration in emerging markets like India and China in Asia shows that there seems to still a lot of steam left in the mobile app development industry.

Not too long ago, Apple added something phenomenal to the iPhone OS: a dashboard screen. If you have a Macintosh computer, you may be familiar with the dashboard that is available (regularly) by pressing F4. Otherwise, you can draw similarities to your Windows 7 Dashboard on the right hand side of your desktop, that shows you updates on your applications and widgets you add to it. Finding your dashboard on your iPhone is just as easy: just put your finger on the top of your iPhone screen, and drag down.

Here, in your dashboard, you will see all of the updates that has been pushed into such by your applications that desire to send you messages: things like new text messages, new updates to your subscribed magazines, your messages on payment applications. If you have reviewed a message set by an application by tapping on it, that message will automatically become deleted. However, if you don’t desire to go into the application to delete it, simply tap in the top right on the bar that categorizes that particular application, and tap again to clear all of the messages set by that application, and clear up your dashboard.

But, your dashboard isn’t all about your application. You not only get your messages, but you get important information set by default applications, such as the weather. If you don’t feel like scouting out your weather application amidst all your applications you have downloaded, simply go into your dashboard, and find out the forecast for the whole week, just by a simple swipe. Not only that, tickers for your stocks are displayed near the bottom of the dashboard.

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.