Big Data analytics and connectivity analytics are crucial tools for gaining value from an Internet of Things (IoT) and Machine-to-Machine (M2M) deployment. But analyzing the application-specific sensor data and connectivity data to obtain useful insights remains a challenge for 72% of executives polled in our recent survey conducted in partnership with research firm Vanson Bourne. We had 300 enterprise-IT decision makers from the United States and the United Kingdom polled to examine the impact of IoT/M2Ms perceived impact on their business. You can see more results from that survey here.
To address this challenge, executives and project managers could refer to the eBook The Definitive Guide to the Internet of Things for Business. A whole chapter of this eBook explains the relevance of analytics, along with five key analytic methods and how they apply to IoT/M2M systems. Even if youre not a data scientist, youll find it helpful to get a basic understanding of how analytics apply to the vast amount of data that IoT/M2M projects create. For example, the Aeris network manages traffic from one billion IoT events each day. The more IoT/M2M data points being transported, the more sophisticated analytics are needed to understand the patterns and make useful business decisions.
Connectivity Analytics for IoT/M2M Deployments
In addition to using advanced analytics to understand the data produced as an end-result of IoT/M2M systems, businesses must manage their own IoT/M2M devices using connectivity analytics. According to the same Vanson Bourne study, 72% of executives agree that management of device connectivity to reduce operational costs is a major priority in the coming year. Device connectivity management is a big priority across the board in all industries, but especially in financial services with an 18% increase in the past two years.
For greater understanding of connectivity analysis, an organization could use Aeris AerVoyance, which provides visibility and insight into its IoT/M2M deployments. Focusing on devices, connectivity, and billing information, this tool helps companies effectively manage their IoT/M2M systems through an intuitive, visual presentation.
AerVoyance identifies devices with connectivity issues and allows zooming in on a specific device, time, or usage activity including data, SMS, voice, sessions, cellular registrations, etc. This allows customers to find specific devices that are behaving abnormally. In addition, there is a summary view of the device portfolio including billing, usage, and status. This type of connectivity analytics tool helps organizations understand aggregate and average connectivity usage over time and better plan deployments.
To find out more about IoT data and analytics, as well topics like scalability, security, and IoT network technology, download the entire eBook.