Information Technology is one of the most dynamic industries with new technologies surfacing frequently. In such a scenario, it can get intimidating for information technology professionals at all levels to keep abreast of the latest technology innovations worth investing time and resources into.

It can therefore get daunting for entry and mid-level IT professionals to decide which technologies they should potentially be developing skills. However, the biggest challenge comes for senior information technology professionals responsible for driving the IT strategy in their organizations.

It is therefore important to keep abreast of the latest technology trends and get them from reputable sources. Here are some of the ways to keep on top of the latest trends in Information Technology.

·         Subscribe to leading Analyst Firms: If you work for a leading IT organization, chances are that you already have subscription to leading IT analyst firms notably Gartner and Forrester. These two firms are some of the most recognized analyst firms with extensive coverage on almost every enterprise technology including hardware and software. These Analyst firms frequently publish reports on global IT spending and trends that are based on primary research conducted on vendors and global CIOs & CTOs. However, subscription to these reports is very expensive and if you are a part of a small organization you may have issues securing access to these reports. One of the most important pieces of research published by these firms happens to be the Gartner Hype Cycle which plots leading technologies and their maturity curve.Even if you do not have access to Gartner research, you can hack your way by searching for “Gartner Hype Cycle” on Google Images and you will in most cases be able to see the plots similar to the one below

Sometimes we have to repeat ourselves before we are heard. Then again there are times where we have to perform a certain action the same way several times before we can carry on with what we want to do.

Repetition is the keyword here and for humans that is something we generally try to avoid. Yet our digital friends love repetition. They never get tired and they never get bored of doing the same thing over and over again countless times.

So it’s little wonder then that all modern programming languages give us various ways in which we can perform a certain action as many times as we need.

In python we have the for statement which gives us the power to loop over large collections of data very quickly and efficiently.

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:

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.”