ABI Research released data this week that forecast global revenues from the integration, storage, analysis, and presentation of Internet of Things (IoT) data to triple over the forecast period and reach US$30 billion in 2021, with a 29.4 percent CAGR.
A key IoT market challenge for enterprises is how to manage, track and analyze all of their data. The proliferation of Internet-connected devices presents a framework for analytics to become much more granular in nature and an opportunity to better align the frequency of reporting to the pace of business operations.
Currently, the biggest challenge lies in managing the variety–rather than the volume or velocity–of IoT data, the general shift from batch- to event-based processing signals a growing interest in real-time / streaming analytics as a lever for IoT value creation.
The need to harmonize these components without creating or simply shifting the bottlenecks that come with the management of high-velocity variable data puts pressure on connectivity providers, edge analytics platform players, and system integrators (SIs) to stand up new and distributed architectures to not only support, but also add value to data at any level.
“Descriptive analytics currently generate more than 75% of IoT analytics revenue,” says Ryan Martin, senior analyst at ABI Research. “But over the next five years, rapid uptake of advanced analytics will overtake descriptive analytics’ share of revenue to the extent that predictive and prescriptive analytics will account for more than 60% of IoT analytics revenue by 2021.”
The general shift from batch to event-based processing signals a growing interest in real-time/streaming analytics as a lever for IoT value creation. ABI Research data analysis suggests that early adoption of predictive and prescriptive analytics is occurring in more developed, mature M2M/IoT verticals.
Growth is aimed at asset-intensive industries in which machinery cost is high, such as within the industrial, manufacturing, field, oil and gas sectors.
“The need to harmonize IoT ecosystem components without creating or simply shifting the bottlenecks that come with the management of high-velocity variable data puts pressure on connectivity providers, edge analytics platform players, and system integrators to stand up new and distributed frameworks,” concludes Martin. “The purpose of these frameworks is to not only support and add value to data, but to also be able to do so at any level.”
Key investments from companies like Cisco, Dell, GE, IBM, Microsoft, PTC, and SAP, as well as a flurry of startup-level vendors like Blue Yonder, mnubo, Mtell, Predixion, and Seeq, further underscores the momentum and importance of analytics in IoT.