It’s the eternal conundrum of a hiring manager – you have to hire for every single position in the company without any first-hand experience. How to do it? If you can have a trusted programmer sit in on the interview, that’s ideal, of course. But what if you’re hiring your first programmer? Or what if you’re hiring a freelancer? Or what if company policy dictates that you’re the only person allowed to do the interviewing? Well, in that case, you need some helpful advice and your innate bullshit detector. We questioned programmers and hiring managers and compiled a list of dos and don’ts. Here are some things to ask when interviewing programmers:

Past Experience

Ask the programmer about the biggest disaster of his career so far, and how he handled it. Did he come in at midnight to fix the code? Was he unaware of the problem until someone brought it up? Did someone else handle it?  According to our programmer sources, “Anyone worth their salt has caused a major meltdown. If they say they haven’t, they’re lying. Or very, very green.” Pushing a code with bugs in it isn’t necessarily bad. Not handling it well is bad.

As usual, your biggest asset is not knowing the field, it is knowing people. Asking about career disasters can be uncomfortable, but if the interviewee is experienced and honest then she won’t have a problem telling you about it, and you will get an idea of how she handles mishaps. Even if you don’t understand what the disaster was or how it was fixed, you should be able to tell how honest she’s being and how she handles being put on the spot.

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 rather unfortunate that in the ever changing and rapidly improving world of technology, we hardly remember the geniuses who through their inventions laid the foundation for many of the conveniences and features we now enjoy in our favorite communication devices.

This article is a tribute to the ten people who made these discoveries and an attempt to bring their achievements into the limelight.

1.      Marty Cooper

Did you know that Cooper was the first to file the patent in 1973, when he was already working for Motorola for the “radio telephone system”. The Cooper’s Law is his brainchild and to think that he himself was inspired to come out with the patent was Star Trek and its Captain Kirk is indeed revealing.

2. Mike Lazardidis
 

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.