Slideshow Gartner's Top Technology Trends for 2016

  • February 10 2016, 5:30am EST
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Gartner's Top 10 Technology Trends for 2016

Data analytics remains one of the top areas of technology investment this year, and most industry watchers expect more of the same in 2016. But analytics is a broad topic, fed by a lot of other top technology trends. David Cearley, vice president and Garner Fellow at Gartner Group, shared his thoughts on the Top 10 Strategic Technology Trends that will impact IT leaders and data analytics in 2016. The list follows.

The Device Mesh

By this, Cearley means the expanding set of endpoints that people use to access applications and information or to interact with other people, social communities, governments and business. "In the post-mobile world the focus shifts to the mobile user who is surrounded by a mesh of devices extending well beyond traditional mobile devices," Cearley says.

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Ambient User Experience

The device mesh creates the foundation for a new continuous ambient user experience, Cearley says. Think of it as one continuous and seamless digital experience for the user that blends device, time, and space, and combines the user's physical environment with the virtual and electronic environments. "Designing these advanced experiences will be a major differentiator for independent software vendors and enterprises alike by 2018," Cearley notes.

3D Printing Materials

The public likes 3D printing, and the public always gets what it wants. That will drive new advances in 3D printing technology, and its wider-scale use in new industries. "3D printing will see a steady expansion over the next 20 years of the materials that can be printed, improvement in the speed with which items can be printed and emergence of new models to print and assemble composite parts," Cearley says.

Information of Everything

"Information has always existed everywhere but has often been isolated, incomplete, unavailable, or unintelligible," Cearley notes. "Advances in semantic tools such as graph databases as well as other emerging data classification and information analysis techniques will bring meaning to the often chaotic deluge of information."

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Advanced Machine Learning

The explosion of data sources and growing complexity of information makes manual classification and analysis infeasible and uneconomic, Cearley stresses. "Deep neural nets (DNNs) automate these tasks and make it possible to address key challenges related to the information of everything trend."

Autonomous Agents and Things

The rise of the machines — or machine learning to be precise — also gives rise to a spectrum of smart machine implementations, Cearley explains. This includes robots, autonomous vehicles, virtual personal assistants, and smart advisors, all acting in an autonomous (or at least semiautonomous) manner. "IT leaders should explore how they can use autonomous things and agents to augment human activity and free people for work that only people can do," Cearley insists.

Adaptive Security Architecture

The complexity of the digital business, along with the rise of a "hacker industry" have raised the stakes for IT security professionals. Perimeter defense is no longer going to cut it, especially with more data and applications going to the cloud. Reaction needs to change to detection. "IT leaders must focus on detecting and responding to threats, as well as more traditional blocking and other measures to prevent attacks."

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Advanced System Architecture

All this talk about the digital mesh and smart machines can't happen without advanced computing architecture, Cearley says. "Systems built on GPUs and FPGAs will function more like human brains that are particularly suited to be applied to deep learning and other pattern-matching algorithms that smart machines use," Cearley says.

Mesh App and Service Architecture

Cearley sees monolithic and linear application designs giving way to a more loosely coupled integrative approach. "Application teams must create new modern architectures to deliver agile, flexible and dynamic cloud-based applications with agile, flexible and dynamic user experiences that span the digital mesh," Cearley observes.

Internet of Things Platforms

IoT platforms complement the mesh app and service architecture, Cearley says. Unfortunately, "Any enterprise embracing the IoT will need to develop an IoT platform strategy, but incomplete competing vendor approaches will make standardization difficult through 2018."