When making a strategic cloud decision, organizations can follow either one of two ideologies: open or closed.

In the past, major software technologies have been widely accepted because an emerging market leader simplified the initial adoption.  After a technology comes of age, the industry spawns open alternatives that provide choice and flexibility, and the result is an open alternative that quickly gains traction and most often outstrips the capabilities of its proprietary predecessor.

After an organization invests significantly in a technology, the complexity and effort required steering a given workload onto a new system or platform is, in most cases, significant. Switching outlays, shifting to updated or new software/hardware platforms, and the accompanying risks may lead to the ubiquitousness of large, monolithic and complex ERP systems – reason not being that they offer the best value for an organization, but rather because shifting to anything else is simply – unthinkable.

There’s no denying that these are critical considerations today since a substantial number of organizations are making their first jump into the cloud and making preparations for the upsetting shift in how IT is delivered to both internal and external clientele. Early adopters are aware of the fact that the innovation brought about by open technologies can bring dramatic change, and hence are realizing how crucial it is to be able to chart their own destiny.

Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied.  For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.

In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.

Panelist,  Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”

Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”

C TRAINING – THE THREE MAIN STAGES OF PROGRAMMING DEVELOPMENT

If you are an aspiring programmer, learning about programming in C is one of the most integral steps of your development.  It is essential that you get the highest quality C training, so that you are well-grounded in the language, and are going to be able to fulfill most of your programming and developmental tasks.  Learning about all aspects of the programming language, including how to fully utilize its portability and design will help you to secure your future in computer programming.  These are some of the concepts you should familiarize yourself with:

·         Major elements of the programming language – This includes things like libraries of functions, using data flow control, and a thourough examination of the basic data types the language is able to address.  As you learn about these fundamental elements, make sure to get practical experience during the course of your C training also, by actually writing programs that follow whatever curriculum you have chosen.

·         Different techniques and other programming elements – Different series of coursework choose to emphasize different things, but try to learn as much as you can about different techniques that are actually employed.  Manipulating both characters and strings, allocating dynamic memory in the proper manner, defining macros, and utilizing the runtime library are all examples of these elements.

IT Outsourcing came to foray as a means for corporations to focus on critical business operations while having a specialized IT company take over the responsibility of managing the IT infrastructure and application development. For corporations especially in the developed countries, IT outsourcing provided two fold advantages, one was access to a highly talented pool of engineers and that too at a lower cost since countries like India were quickly growing their stature as an IT outsourcing hub.

IT Outsourcing is now as mainstream as ever and almost every leading organization outsources some or all parts of its IT infrastructure to a specialized company. It makes pure business sense and with tightening budget controls, IT outsourcing has become one of the strategic cost reduction driver for most organizations. Moreover, IT outsourcing is no more restricted to companies in USA & Europe outsourcing their IT projects to countries like India. Domestic companies within India itself actively use IT outsourcing including the Indian government like the India Post project given to TCS.

Is it then a no brainer that IT Outsourcing is critical to your business? Well, if it is cheaper and does not seem to have any inherent disadvantages why not!! Not really, IT Outsourcing despite proven benefits has its limitations and you should be cognizant be of the same before considering outsourcing your IT operations.

·         Limitations in estimating the actual cost of IT outsourcing:Let’s tackle the biggest driver of IT Outsourcing-Cost Savings. For anyone to estimate the cost savings from IT Outsourcing one needs to be able to predict the cost of outsourcing which then helps understand the cost savings from the same. Yes, at a higher level it is a matter of a simple $ per man-hour costs and IT outsourcing will appear to be cheaper in almost all cases. However, “hidden costs” are commonplace with IT outsourcing and it can be immensely difficult to accurately predict these hidden costs. For example, you need to be able to identify the costs of transitioning your in-house IT to an outsourcer, management overhead needed to manage the outsourcing relationship etc. In addition, IT outsourcing contracts are fixed at the start of the contract and as a result any additional requirement/change tends to be charged additionally. It is no surprise that IT requirements can change frequently and if your outsourcing contract doesn’t account for flexibility, you might be limited in the actual cost savings you might make. There is no surprise that there have been so many instances of IT outsourcing projects overshooting their budgets by a huge margin such as the one government shared services project going 500 million pounds over budget