As part of our C++ Tutorials series, here is a free overview of C++ pointers you may enjoy and find beneficial.

C++ Pointers Tutorials

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.

Python and Ruby, each with roots going back into the 1990s, are two of the most popular interpreted programming languages today. Ruby is most widely known as the language in which the ubiquitous Ruby on Rails web application framework is written, but it also has legions of fans that use it for things that have nothing to do with the web. Python is a big hit in the numerical and scientific computing communities at the present time, rapidly displacing such longtime stalwarts as R when it comes to these applications. It too, however, is also put to a myriad of other uses, and the two languages probably vie for the title when it comes to how flexible their users find them.

A Matter of Personality...

That isn't to say that there aren't some major, immediately noticeable, differences between the two programming tongues. Ruby is famous for its flexibility and eagerness to please; it is seen by many as a cleaned-up continuation of Perl's "Do What I Mean" philosophy, whereby the interpreter does its best to figure out the meaning of evening non-canonical syntactic constructs. In fact, the language's creator, Yukihiro Matsumoto, chose his brainchild's name in homage to that earlier language's gemstone-inspired moniker.

Python, on the other hand, takes a very different tact. In a famous Python Enhancement Proposal called "The Zen of Python," longtime Pythonista Tim Peters declared it to be preferable that there should only be a single obvious way to do anything. Python enthusiasts and programmers, then, generally prize unanimity of style over syntactic flexibility compared to those who choose Ruby, and this shows in the code they create. Even Python's whitespace-sensitive parsing has a feel of lending clarity through syntactical enforcement that is very much at odds with the much fuzzier style of typical Ruby code.

For example, Python's much-admired list comprehension feature serves as the most obvious way to build up certain kinds of lists according to initial conditions:

a = [x**3 for x in range(10,20)]
b = [y for y in a if y % 2 == 0]

first builds up a list of the cubes of all of the numbers between 10 and 19 (yes, 19), assigning the result to 'a'. A second list of those elements in 'a' which are even is then stored in 'b'. One natural way to do this in Ruby is probably:

a = (10..19).map {|x| x ** 3}
b = a.select {|y| y.even?}

but there are a number of obvious alternatives, such as:

a = (10..19).collect do |x|
x ** 3
end

b = a.find_all do |y|
y % 2 == 0
end

It tends to be a little easier to come up with equally viable, but syntactically distinct, solutions in Ruby compared to Python, even for relatively simple tasks like the above. That is not to say that Ruby is a messy language, either; it is merely that it is somewhat freer and more forgiving than Python is, and many consider Python's relative purity in this regard a real advantage when it comes to writing clear, easily understandable code.

And Somewhat One of Performance

Companies have been collecting and analyzing data forever, pretty much.” So what’s really new here? What’s driving the data-analytics revolution and what does it mean for those that choose to postpone or ignore the pivotal role big-data is currently having on productivity and competition globally?

General Electric chairman and CEO Jeff Immelt explains it best when stating that “industrial companies are now in the information business—whether they like it or not.”  Likewise, digital data is now everywhere, it’s in every industry, in every economy, in every organization and according to the McKinsey Global Institute (MGI), this topic might once have concerned only a few data geeks, but big data is now relevant for leaders across every sector as well as consumers of products and services.

In light of the new data-driven global landscape and rapid technological advances, the question for senior leaders in companies now is how to integrate new capabilities into their operations and strategies—and position themselves globally where analytics can influence entire industries. An interesting discussion with six of theses senior leaders is covered in MGI’s article, “How companies are using big data and analytics,” providing us with a glimpse into a real-time decision making processes.