Analytics of Things Market
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.
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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.
Most of the IoT vendors in the market have offerings for IoT analytics as well. The major vendors in the IoT market are Microsoft, Cisco, SAP, Intel, IBM, Google, AGT International, Accenture, Capgemini, and TIBCO Software.
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Analytics 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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The value of IoT Analytics lies in real-time business analytics. In IoT, real-time analysis is difficult with several million events often streaming into the system. Lack of real-time advanced algorithms poses a challenge in real-time analytics. However, the challenges are being addressed as several IoT vendors are investing in improving the efficiency of the IoT systems. Descriptive analytics has already become mature, and the vendors are now focusing on predictive and prescriptive analytics. Both the types are likely to attract consumers’ attention due to high operational efficiencies and cost reductions that they yield.
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Key questions answered in the report include:
What will the market size and the growth rate by the end of the forecast period?
What are the key industry trends impacting the growth of the market?
What are the key factors driving and restraining the Analytics of Thingsmarket?
What are the challenges to market growth?
In the end, The main goal of this research study is to provide a clear picture and a better understanding of the market to the manufacturers, suppliers, and the distributors operational in it. The readers can gain a deep insight into this market from this piece of information that can enable them to formulate and develop critical strategies for the further expansion of their businesses.
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