In the coming years, the deluge of data from internet connected sensors and other devices will be significant. The revenues generated from integrating, storing, analyzing, and presenting Internet of Things (IoT) data will reach $5.7 billion in 2015, according the the latest global market study by ABI Research.
In the next 5 years, ABI believes that the market will expand dramatically, to an extent that in 2020 it's estimated to account for nearly one-third of all big data and analytics revenues.
"About 60 percent of this year’s revenues come from three key areas -- energy management, security management, as well as monitoring and status applications," said Aapo Markkanen, principal analyst at ABI Research.
Within these segments, there are 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).
According to ABI's assessment, these early growth drivers also have in common the fact that the economics of IoT connectivity align easily enough with the requirements of analytic modelling.
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 the growth of start-up level activity -- aimed at filling the apparent gaps in the market.
ABI says what's truly remarkable about this market is how much of the innovation actually comes from new start-ups. Take, for instance, the ParStream geo-distributed architecture, the Cyberlightning 3D visualization technology, or the Peaxy 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 likes of Datawatch, Informatica, Software AG, and Splunk seem well-positioned to seize the emerging IoT big data opportunity.
In the next 5 years, ABI believes that the market will expand dramatically, to an extent that in 2020 it's estimated to account for nearly one-third of all big data and analytics revenues.
"About 60 percent of this year’s revenues come from three key areas -- energy management, security management, as well as monitoring and status applications," said Aapo Markkanen, principal analyst at ABI Research.
Within these segments, there are 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).
According to ABI's assessment, these early growth drivers also have in common the fact that the economics of IoT connectivity align easily enough with the requirements of analytic modelling.
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 the growth of start-up level activity -- aimed at filling the apparent gaps in the market.
ABI says what's truly remarkable about this market is how much of the innovation actually comes from new start-ups. Take, for instance, the ParStream geo-distributed architecture, the Cyberlightning 3D visualization technology, or the Peaxy 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 likes of Datawatch, Informatica, Software AG, and Splunk seem well-positioned to seize the emerging IoT big data opportunity.