When it comes to making sense of data, getting actionable insights is the holy grail. But what does this even mean? When is a finding an insight? When is an insight actionable? Let's get to the bottom of this by looking at some examples.

The customer service agent on the other end of the phone may seem oblivious to your growing ire, but the computer recording your call isn’t. More and more, companies are using the science of voice analytics to gain insight into customer interactions, identification even lie detection.

Every day students deal with piles of papers and many-page documents, but don’t have much time to read them all. However, thanks to the rapid development of technologies, they can relish an array of solutions, among which are mobile apps able to analyze and summarize texts to the needed size. Here are 8 mobile apps for text analysis.

Gartner has officially released the 2016 version of their Magic Quadrant for Business Intelligence and Analytics Platforms, and boy has the market changed. According to Gartner, the enterprise analytics industry has surpassed the tipping point, and has nearly finished its evolution from a market based heavily on reporting to

You could say we've been working toward the internet of things (IoT) since computers were first invented. Look at how airplanes have changed from flying by wire to now, quite literally, flying by IoT (or connected plane).

The connected car is another example of how big data analytics is the driving force behind the application of all things IoT. This is why I believe big data analytics had to evolve first, prior to tackling all the cool issues, services and products being driven by IoT.

One of my management principles is “passion for the mission is not optional.” To me, it’s critical that people believe in what we’re doing. In fact, I think the whole team believing in the mission is more important than having the exact right skills on the team. Culture eats strategy and passion beats talent.

Do you want to work in data? What does this mean? For the last there years I was at one of the coolest companies in the data space: LinkedIn! LinkedIn has amazing data assets and they have been at the forefront of data science. I want to share what I see as the three key tasks of a Director of Data Science: insights, tools & innovation.

If you’ve ever had to call a customer help line or other call center, you probably experience a shiver of dread at the mere thought. Some customer help lines are so reviled that people would rather deal with the issues than try to get support.