Analytic of Things (AoT) expected to Grow with a Healthy CAGR

New wireless technologies, sensors, and mobile devices are driving the IoT evolution. However, the real business value of the technology lies in analytics. Advanced analytics can provide meaningful insights that could help in transforming consumer experiences, development of products and services, optimization of operations, and cost savings on assets. The datasets extracted from sensors can be correlated with data, such as social data, to yield a strong understanding of the operations or a person or a group of individuals.

Product analysis
IoT analytics platform could enable a wide range of analytics, from real-time to machine learning and cognitive to edge. Automated machine learning can be added to quick and simple real-time monitoring for identification of anomalous behavior. Predictive analytics uses advanced statistical modeling and historic data. For contextual insights, cognitive analytics can be applied to the unstructured data sources. These insights would consist of detailed graphs and visualization dashboards. The platform is purposely built to scale the high velocity and large volumes of data. With the advancements in processing and analytics, analytics can be performed at the edge of the network to overcome the challenges of connectivity, security, bandwidth, and latency.

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Market analysis
Analytic of Things (AoT) has become highly relevant to few industries such as manufacturing, logistics, and utilities. Analytics is being applied to power grid systems for continuous monitoring, proactive management of power supply, and preventive maintenance. Most of the manufacturing plants and fleets in logistics already have Internet-enabled sensors, and thus these businesses utilize analytics. Most of the new business processes and systems are likely to incorporate at least some elements of IoT analytics. Large enterprises who have prioritized low cost solutions are likely to deploy AoT solutions on cloud.

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