Big data is a factor that will, to a large extent, determine the future growth rate in the M2M industry. Without adequate analytics, and the right practices to take advantage of it, the companies rolling out M2M solutions will be destined to be stuck in the lower realms of applications: monitoring, reporting, and simple rules-based actions. These are worthy areas by their own merit, but the value that can be extracted from them does not necessarily justify large-scale sensor and connectivity deployments. This issue should not also be overlooked when discussing why M2M has not previously managed to evolve as fast as has been generally anticipated. The value of machine data has not, in many use cases, justified the cost of its extraction.
In this technology analysis, ABI Research will explore how big data and analytics are being applied in the M2M industry and what role they can be anticipated to play in the M2M value chain. The first part of the study provides an overview of a standard analytics process and its components, while the second part presents ABI Research's relevant market forecasts. The market's revenues are broken down by industry vertical, segment (data integration, data storage, core analytics, and data presentation), besides which the revenues in the core analytics segment are split by analytics phase (descriptive, predictive, and prescriptive). Included is also a forecast on the installed base of analytics-enabled M2M connections. Finally, the third part of the report examines the leading use cases for M2M analytics and the vendor landscape.