Communication is one of the main objectives that an organization needs to have in place to stay efficient and productive. A breakdown in accurate and efficient communication between departments at any point in the organization can result in conflict or loss of business.  Sadly, the efficiency between different departments in an organization becomes most evident when communication breaks down. As an example, David Grossman reported in “The Cost of Poor Communications” that a survey of 400 companies with 100,000 employees each cited an average loss per company of $62.4 million per year because of inadequate communication to and between employees.

With the dawning of the big-data era and the global competition that Machine Learning algorithms has sparked, it’s more vital than ever for companies of all sizes to prioritize departmental communication mishaps. Perhaps, today, as a result of the many emerging markets, the most essential of these connections are between IT and the business units. CMO’s and CIO’s are becoming natural partners in the sense that CMO’s, in order to capture revenue opportunities, are expected to master not just the art of strategy and creativity but also the science of analytics. The CIO, on the other hand, is accountable for using technical groundwork to enable and accelerate revenue growth. Since business and technology people speak very different languages, there’s a need on both sides to start sharing the vocabulary or understanding of what is expected in order to avoid gridlock.

In the McKinsey article, Getting the CMO and CIO to work as partners, the author speaks to five prerequisite steps that the CMO and the CIO can take in order to be successful in their new roles.

--- Be clear on decision governance
Teams should define when decisions are needed, what must be decided, and who is responsible for making them.

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.

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

 Unlike traditional online courses that charge a fee, limit enrollment and provide credit or certification, Moocs (massive open online courses) are usually free or low cost and can host hundreds of  thousands global participants.  Although MOOC have been around for years in the form of collective techie learning gatherings, participation in 2012 has ballooned at a rapid pace likened to FaceBook in its heyday.  According to The Year of the MOOCarticle in the New YorkTimes, edX, a nonprofit start-up backed by Harvard and MIT, had 370,000 registrants in the fall of its first official courses. This paled in comparison to the amount of students that Courseraattained in its first year of online learning opportunities, 1.7 million!

Will MOOCs Replace education as we know it?

Like any new trend, massive participation in online classes has its challenges. Lynda Weinman has ample experience when pointing out that they are by no means a replacement for formal education.  As a former digital animator, special effects designer and classroom college teacher, Linda paved the path for an earlier version of MOOC education in the mid 90’s when she founded Lynda.comas an aide to her own students. Over four million students and 2,200 courses later she’s confident when clarifying that many of the collegespartnered with Lynda.com use the tutorials as added features to their existing courses.  When asked in an interview with ReadWriteBuilders, if high technical companies look at online programs in terms of advancement as a supplement to traditional education or as a way for people to further their careers, Lynda feels that “it’sjust one example of something that you can do to enhance your attractiveness to potential employers. But [it’s also important to have] a portfolio and body of work, references that actually work out, showing that you had success in the past.”

MOOC Benefits: