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.

It is said that spoken languages shape thoughts by their inclusion and exclusion of concepts, and by structuring them in different ways. Similarly, programming languages shape solutions by making some tasks easier and others less aesthetic. Using F# instead of C# reshapes software projects in ways that prefer certain development styles and outcomes, changing what is possible and how it is achieved.

F# is a functional language from Microsoft's research division. While once relegated to the land of impractical academia, the principles espoused by functional programming are beginning to garner mainstream appeal.

As its name implies, functions are first-class citizens in functional programming. Blocks of code can be stored in variables, passed to other functions, and infinitely composed into higher-order functions, encouraging cleaner abstractions and easier testing. While it has long been possible to store and pass code, F#'s clean syntax for higher-order functions encourages them as a solution to any problem seeking an abstraction.

F# also encourages immutability. Instead of maintaining state in variables, functional programming with F# models programs as a series of functions converting inputs to outputs. While this introduces complications for those used to imperative styles, the benefits of immutability mesh well with many current developments best practices.

For instance, if functions are pure, handling only immutable data and exhibiting no side effects, then testing is vastly simplified. It is very easy to test that a specific block of code always returns the same value given the same inputs, and by modeling code as a series of immutable functions, it becomes possible to gain a deep and highly precise set of guarantees that software will behave exactly as written.

Further, if execution flow is exclusively a matter of routing function inputs to outputs, then concurrency is vastly simplified. By shifting away from mutable state to immutable functions, the need for locks and semaphores is vastly reduced if not entirely eliminated, and multi-processor development is almost effortless in many cases.

Type inference is another powerful feature of many functional languages. It is often unnecessary to specify argument and return types, since any modern compiler can infer them automatically. F# brings this feature to most areas of the language, making F# feel less like a statically-typed language and more like Ruby or Python. F# also eliminates noise like braces, explicit returns, and other bits of ceremony that make languages feel cumbersome.

Functional programming with F# makes it possible to write concise, easily testable code that is simpler to parallelize and reason about. However, strict functional styles often require imperative developers to learn new ways of thinking that are not as intuitive. Fortunately, F# makes it possible to incrementally change habits over time. Thanks to its hybrid object-oriented and functional nature, and its clean interoperability with the .net platform, F# developers can gradually shift to a more functional mindset while still using the algorithms and libraries with which they are most familiar.

Related F# Resources:

F# Programming Essentials Training

With an ever increasing rise in the use of employment testing, certification testing and need to get a degree, I thought I would write this basic guide on how to study for exams.  Although it was originally written with the college student in mind, the fundamentals still apply to all of us in the workforce.

There are few things that strike terror into the hearts of students more than exam day, particularly if they have inadequate study skills. Perhaps these students study for hours and hours, only to discover that by exam time they've forgotten everything they've read. Below are a few study tips to help struggling students remember the information they've reviewed for their exams. 

-Use memory tricks. There are a number of memory tricks that you can use to help you remember large amounts of information. For example, the use of acronyms (such as Roy G Biv to remember the colors of the rainbow) can be very helpful. In addition, you can use visualization techniques, similes, and songs to assist you in recalling your study material.

-Don't cram. Your brain requires time to absorb facts. If you know about a test in advance, start studying right away for a little bit every day, ramping up your efforts as the exam approaches.

-Take frequent breaks while studying. It may seem counter-intuitive that spending less time studying might actually help you remember more of what you've read. But taking appropriately timed study breaks will keep your mind fresh and make sure you don't stress too much.

-Write it out. For many people, writing information down as they read it is the best way to learn it. Don't just write exactly what you read, however; by rewording the information or even drawing a picture or diagram you commit it to your memory in more than one way, allowing you to remember it easier later.

-Teach it to a friend. To remember information, you have to understand it. And in order to teach information, you need to understand it as well. Nothing tests your ability to recall facts better than teaching them to another person. Find a friend unfamiliar with your study material and teach them a lesson in the subject.

-Get plenty of sleep the night before the exam. Finally, be sure to get a good night's rest the night before you take the exam. Falling asleep at your desk will accomplish nothing. This will help you be more alert while you are taking your test, and will allow you to retain more information.

 

Before we go to the list do you know what makes software skills most sought-after and hence more valuable than most of the other job skills? It is simply because unlike any other skill, software skills are global and are not at all location specific! With the evolution and penetration of internet technologies, the physical distance between the client and service provider hardly matters. So, with more advancement in technology, it is indeed going to rain opportunities on the right skilled developer. I’ll take the liberty to reproduce the following quotes here to prove my claims statistically:

Demand for “cloud-ready” IT workers will grow by 26 percent annually through 2015, with as many as 7 million cloud-related jobs available worldwide.

---IDC White Paper (November 2012).

In the United States, the IT sector is experiencing modest growth of IT jobs in general, with the average growth in IT employment between 1.1 and 2.7 percent per year through 2020.

---U.S. Bureau of Labor Statistics.