The 3 Ds of the Internet of Things

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Adobe customer Under Armour debuted the feature at the Digital Marketing Summit using a smartphone and a TV screen, but the tool works just as well sharing the display between, say, a smart watch app and an in-store iPad. And it's not just a resource for retailers—Stark maintains that use cases span industries. A driver interested in a new car insurance policy, for example, can come to a location and transfer the quote she's viewing on her mobile device to an agent's display screen instantly.

"There's a lot of talk about how these 'connected things' are going to serve as new pathways for personalized interactions with customers, and that's very true, but if these channels are disjointed, the interactions will be repetitive or irrelevant," Stark says. "Before you can even think about customizing and personalizing experiences across different channels, you have to ensure that those channels are connected," she adds.

Other vendors have made IoT investments that reach beyond traditional screens. A market with huge potential for IoT innovation is the automotive industry; with more than 100 million vehicles shipped annually, connected cars present a vast opportunity, Oracle CEO Mark Hurd noted at the company's Modern Customer Experience conference in April.

"The connected car is already a reality, and in-vehicle wireless connectivity is rapidly expanding from luxury models and premium brands to high-volume midmarket models," James Hines, research director at Gartner, said in a statement. "The increased consumption and creation of digital content within the vehicle will drive the need for more sophisticated infotainment systems, creating opportunities for application processors, graphics accelerators, displays, and human-machine interface technologies," Hines added. Though Hurd offered few details, he insisted that Java, Oracle’s standardized software platform for machine-to-machine communication, will play a key role in adding this kind of technology to cars.


Though vendors have made strides in helping companies build sophisticated networks between devices, connecting things is one part of the challenge. Despite the buzz surrounding the premise of a connected world where the refrigerator knows you're out of milk before you do, the reality is that the Internet of Things is going to generate a tremendous amount of data that few vendors and even fewer companies will know how to handle.

The challenge, analysts agreed at the Gartner Business Intelligence Summit, is that companies are trying to fit a whole new kind of data into a traditional data ecosystem. Databases have come a long way—many are now more agile than they've ever been. Unique environments such as Hadoop allow for the quick processing of very large and often unstructured data, while powerful in-memory solutions from legacy vendors including Oracle and SAS make real-time decision making a reality. There's a growing need for these data processing capabilities, but there's also a need for something more.

Gartner analyst Dan Sommer pointed to an evolution occurring in the business intelligence market. Data is being created at such a rate that eventually traditional data processing tools will not be able to keep up without predictive and prescriptive capabilities. As predictive and prescriptive technology outpaces standard analytics, data science will become less reliant on business intelligence and lean more on algorithmic, or artificial, intelligence, according to Sommer. "We're living in a world of data collection," he said, "but the future calls for data connection. To connect data that's being produced at this magnitude, we're going to need technology and solutions that stay several steps ahead. That requires algorithms and machine learning."

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