The Internet of Things (IoT) and analytics software for the most part remain separate islands. But over time, more IoT systems will connect with analytics workloads that are distributed over networks, according to ABI Research.

The volume of data captured by Internet of Things (IoT)-connected devices exceeded 200 exabytes in 2014, the market research said. And the firm forecasts that the annual total will grow seven-fold by the decade’s end, surpassing 1,600 exabytes—or 1.6 zettabytes—in 2020.

“The data originating from connected products and processes follows a certain journey of magnitudes,” Aapo Markkanen, principal analyst at ABI, said in a statement. “The yearly volumes that are generated within endpoints are counted in yottabytes, but only a tiny fraction of this vast data mass is actually being captured for storage or further analysis.”

Of the captured volume, on average more than 90% is stored or processed locally without a cloud element, Markkanen said. So far, the local data stores have typically been largely inaccessible for analytics, but that is now starting to change, he said.

In terms of deployment architectures, the IoT is currently undergoing a major paradigm shift from cloud computing toward edge computing, the report said. This shift is opening up edge-based data to meaningful analysis, by distributing the analytic workloads across the network.

“Edge computing is a huge challenge for the entire IoT value chain, as we can see from the way that cloud platforms, analytics vendors, and gateway suppliers are scrambling to collaborate with each other,” Dan Shey, practice director at ABI, said in a statement. “It is also a great opportunity for various software and hardware players that have been working towards this goal even far before the IoT as a concept became fashionable.”

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