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:

One of the biggest challenges in pursuing a career in software development is to figure out which language you want to work. In addition to commonly used software programming languages like C, C++, C# and Java a lot of new programming languages such as Python, Ruby on Rails have surfaced especially because they are used by a lot of consumer based start-ups these days.

It could then be a daunting task to figure out the technical language you should learn which helps you prosper in a software engineering career no matter the technology advancements that happen in the marketplace. Learning a fundamental and universal language like C# could be a great start to your career as the language is very mature and extensively used by companies large and small

What is C#

Similar to Java, C# is a multi-paradigm, object oriented language developed by Microsoft. C# is intended for use in developing software components meant to be deployed in distributed environments. So in essence, learning C# can enable you to write applications for large and complex server side systems that use sophisticated operating systems as well as compact mobile operating systems such as Android

Technology is wonderful. It helps us run our businesses and connects us to the world. But when computer problems get in the way of getting what you need to get done, you can go from easygoing to mad-as-a-hornet in 3 seconds flat. Before you panic or give in to the temptation to throw your computer out the window, try these easy fixes.

5 Common Computer Problems

1. Sluggish PC

A sluggish PC often means low disk space caused by an accumulation of temporary Internet files, photos, music, and downloads. One of the easiest fixes for a slow PC is to clear your cache.

The way you’ll do this will depend on the Internet browser you use:

• Chrome– On the top right-hand side of the screen, you’ll see what looks like a window blind. Click on that. Click on ‘History’ and hit ‘Clear Browsing Data’.

• Safari– On the upper left-hand side, you’ll see a tab marked ‘Safari’. Click on that. Scroll down and hit ‘Empty Cache’.

• Internet Explorer– Click on ‘Tools’ and scroll down to ‘Internet Options’. Under ‘Browsing History’ click ‘Delete’. Delete files and cookies.

• FireFox – At the top of the window click ‘Tools’ then go to ‘Options’. Select the ‘Advanced’ panel and click on the ‘Network’ tab. Go to ‘Cached Web Content’ and hit ‘Clear Now’.

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?