The creation and consumption of data continues to grow by leaps and bounds and with it the investment in big data analytics hardware, software, and services and in data scientists and their continuing education. The availability of very large data sets is one of the reasons Deep Learning, a sub-set of artificial intelligence (AI), has recently emerged as the hottest tech trend, with Google, Facebook, Baidu, Amazon, IBM, Intel, and Microsoft, all with very deep pockets, investing in acquiring talent and releasing open AI hardware and software.

Gartner analyst Brian Blau testifies about augmented reality to the Senate and highlights the potential for AR technology.

Imagine a world in which field service workers who maintain utilities will be able to use an augmented reality (AR) headset to provide visual overlays of complex instructions over their work on physical structures. During a “hands busy” task, AR would allow for greater efficiency and improved productivity.

As part of the mission of improving the customer experience, it is important to have measurement and monitoring tools in place that can provide real-time insights into metrics the customer finds important.

There are still customers of banks and members of credit unions who visit the branch office. For a variety of reasons, these bricks and mortar visitors favor personal over automated service.

Businesses are collecting more data about their operations and their customers than ever before. But data in itself is only part of the story. For it to be useful it's necessary to spot patterns and gain insights.

At this point most businesses turn to analytics, but this can only tell you what's happened in the past. To predict future trends means using algorithms to build models of what may be complex systems.

Wait a second. Before you read any further, answer this: what made you click on this article?

Was it a rational choice that involved a cost-benefit calculation of how much time you’re going to spend reading it versus the valuable insights you might gain? Or did you just have a gut feeling that this article would be interesting?

Emotion analytics promises new insight into true feelings lurking behind facial expressions.

Emerging Apps for Emotion Analytics:

• Test movie trailers for emotional impact.
• Detect patient depression and pain.
• Recognize when drivers fall asleep at the wheel.
• Aid in business negotiations over video chat.

A Q&A with Gartner’s Mike Ramsey explores the road to driverless mobility.

There is tremendous buzz surrounding autonomous and connected vehicles, and the ecosystem of technology that is feeding them. Gartner forecasts 21 million new automobiles will be equipped with data connectivity, either through a built-in communications module or tethered to a mobile device in 2017.

CDOs must unify data management and analytics across the organization.

The transition to digital business requires chief data officers (CDOs) to shift their organizational mindset. They need to align and coordinate a wide variety of data management and analytics initiatives to enable innovation, drive efficiencies and meet their business objectives.