foundation for an increasing number of M2M business cases. In essence, such analytics-driven business cases will be about making previously opaque physical assets part of the digital data universe. M2M has thus a very synergistic relationship with the wider big data space, with growth in one industry driving also growth in the other."

Significantly, the actual value of M2M data can vary greatly by the depth of delivered analysis. At the moment, most enterprises with relevant data assets are trying to migrate from descriptive and diagnostic insights to predictive analytics. Mastering the predictive phase could then ultimately lead to the final, prescriptive phase of analytics.

Practice director Dan Shey says, "Predictive analytics is becoming one of the hottest areas in the M2M value chain. Of today's analytics establishment, SAP and IBM have woken up to the opportunity reasonably early. Of the younger companies, Splunk is an example of a firm that could develop into a true Internet of Things powerhouse if it plays its cards right. Given the far-reaching possibilities of machine learning, we are also expecting major impact from players that successfully apply it to industrial settings. Mtell appears to be making strides in this field, and going forward also Grok will be one to watch."

These findings are from ABI Research's "Big Data and Analytics in M2M Services" study, which is part of the firm's M2M Service Delivery Platforms and Cloud Content and Services Research Services.

Source: ABI Research