Mobile network service providers are going to be inundated with machine-to-machine (M2M) data. Extracting meaning and value from that mass of raw information is a huge undertaking. Analytics software platforms and professional services are part of the solution.
ABI Research forecasts that the M2M analytics industry will grow a robust 53.1 percent over the next 5 years -- from $1.9 billion in 2013 to $14.3 billion in 2018.
The ABI forecast includes revenue segmentation for the five components that together enable analytics to be used in M2M services: including data integration, data storage, core analytics, data presentation, and associated professional services.
"Analytics will play a critical role in the evolution of M2M, serving as the foundation for an increasing number of M2M business cases," said Aapo Markkanen, senior analyst at ABI Research.
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 synergetic 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.
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, ABI says they're also expecting a major impact from players that successfully apply it to industrial settings. Mtell appears to be making strides in this field, and going forward Grok will also be one to watch.
ABI Research forecasts that the M2M analytics industry will grow a robust 53.1 percent over the next 5 years -- from $1.9 billion in 2013 to $14.3 billion in 2018.
The ABI forecast includes revenue segmentation for the five components that together enable analytics to be used in M2M services: including data integration, data storage, core analytics, data presentation, and associated professional services.
"Analytics will play a critical role in the evolution of M2M, serving as the foundation for an increasing number of M2M business cases," said Aapo Markkanen, senior analyst at ABI Research.
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 synergetic 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.
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, ABI says they're also expecting a major impact from players that successfully apply it to industrial settings. Mtell appears to be making strides in this field, and going forward Grok will also be one to watch.