Principal analyst Aapo Markkanen says, “About 60 percent of this year’s revenues come from three key areas: energy management, security management, as well as monitoring and status applications. Within these segments, we can generally find analytic applications that reduce the cost base of asset-intensive operations (condition-based maintenance), automate routine workflows (surveillance), or even enable new business models (usage-based insurance). These early growth drivers also have in common the fact that the economics of IoT connectivity align easily enough with the requirements of analytic modeling.”
Making sense of IoT-kind data from machines and sensors data comes often with its unique challenges, such as the need for time-series databases in storage, and for relatively deep domain expertise in analysis. These kinds of factors create a certain mismatch with many leading technologies that have been designed for more traditional, “digital-first” analytic environments. This, in turn, is attracting a flurry of start-up-level activity aimed at filling the gaps.
According to practice director Dan Shey, “What is remarkable about this market is how much of the innovation actually comes from start-ups. Take, for instance, ParStream’s geo-distributed architecture, CyberLightning’s 3D visualization technology, or Peaxy’s work on software-defined data access. All three address some of the problems that usually come up in discussions with end-users. Meanwhile, of the more incumbent vendors, Datawatch, Informatica, Software AG and Splunk seem well-positioned to seize the IoT opportunity.”
Source: ABI Research
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