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Can Mobile Operators Tap the US$5.7 Billion IoT/M2M Driven Big Data Analytics Market?

14 January 2015
(2 votes)
Can Mobile Operators Tap the US$5.7 Billion IoT/M2M Driven Big Data Analytics Market? Image Credit: PCC Mobile Broadband

Ability to wirelessly transfer information to and from otherwise unconnected devices such as the coffee machine, the garage door, the industrial equipment and the power meter is what fueled the initial excitement on the Internet-of-Things (IoT) and machine-to-machine (M2M) communications. While wireless transfer of information from machine to machine allowed images from a remote camera, readings on a remote thermometer and the location of an entire commercial fleet to be transmitted over the air, what really made IoT and M2M the focus of many businesses across all sectors of the economy today is how the timely growth in big data technologies enabled data collected from all the M2M end-nodes to be processed into valuable information and insights that then started fueling new revenue streams and business opportunities for these businesses.

Big data analytics have enabled raw data collected in huge data lakes across data centres to be filtered, processed and extracted into other applications. Businesses, leveraging cloud services are able to cost effectively manage the collection of data, store the data securely in their data reservoirs, deploy required computing resources and produce the information which is later used as input across all their business processes. In the case of IoT/M2M, the processed information is channelled back in almost real-time onto applications that are accessed by end users - both enterprises and also retail customers - on a multitude of end terminals including computers and mobile devices. Without big data, most IoT/M2M applications will not be producing the real-time insights necessary for end users to control and manage the M2M devices/appliances remotely.

IoT/M2M will hence become one of the biggest growth drivers for big data analytics.  According to ABI Research, revenues from integrating, storing, analyzing, and presenting Internet of Things (IoT) data will reach US$5.7 billion in 2015. The firm expects the growth to intensify over the next five years, resulting in IoT/M2M accouting for nearly one-third of all big data and analytics revenues by 2020. Data generated by IoT/M2M however, brings with it a few challenges as it differs substantially from traditional data. ABI Research said that IoT-type data requires time-series databases in storage and equally competitive expertise in analysis and pointed out that there are a number of startups who have started offering big data solutions specifically for IoT/M2M applications, which can be deployed by IoT/M2M service providers to drive their services. At the same time, incumbents, specifically telecom operators will be watching this space with much interest as it presents opportunities for Operators to offer big data analytics as a service for enterprise customers who are already using the operators' network and datacenter services for connectivity and storage of information collected from thousands (and sometimes millions) of their M2M devices. Operators are also the connectivity providers for end-users of the M2M applications, such as Smart Home Apps or the Connected Car Apps, whose inputs are provided by these analytics. By merging connectivity services (to the M2M nodes as well as the end-user mobile devices), cloud services (data storage and computing) and big data analytics, Operators will be able to deliver integrated and fully fledged IoT/M2M solutions for a wide range of applications in this fast growing segment. 

Principal analyst Aapo Markkanen
About 60% of this year’s revenues come from three key areas: energy management, security management, as well as monitoring and status applications. Within these segments, we can generally find analytic applications that reduce the cost base of asset-intensive operations (condition-based maintenance), automate routine workflows (surveillance), or even enable new business models (usage-based insurance). These early growth drivers also have in common the fact that the economics of IoT connectivity align easily enough with the requirements of analytic modelling.

Dan Shey, Practice Director
What is remarkable about this market is how much of the innovation actually comes from startups. Take, for instance, ParStream’s geo-distributed architecture, Cyberlightning’s 3D visualization technology, or Peaxy’s work on software-defined data access. All three address some of the problems that usually come up in discussions with end-users. Meanwhile, of the more incumbent vendors likes of Datawatch, Informatica, Software AG, and Splunk seem well-positioned to seize the IoT opportunity.

Executive Editor of The Fast Mode | 5G | IoT/M2M | Telecom Strategy | Mobile Data Innovations 

Tara Neal covers stories on strategies and initiatives in the Digital Telco space, and anchors the 5G and IoT/M2M verticals on the publication. Tara holds a First Class Honours in BSc Accounting and Finance from The London School of Economics, UK and is a CFA charterholder from the CFA Institute, United States. Tara has over 20 years experience in technology and business strategy.

Follow her on Twitter @taraneal11, LinkedIn @taraneal11, Facebook or email her at [email protected].

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