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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.

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