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IoT Analytics Market is Anticipated to Show the Robust Growth During 2016 - 2026

Press Release   •   Feb 09, 2017 02:23 EST

Internet of things or connected devices is driving innovation across all industries. Moreover, as connected devices are gaining rapid popularity, amount of data being generated is increasing too, out of which only some parts are important and need to be analyzed. Many enterprises are starting to realize the importance of data generated from IoT devices, which can help implement better informed business decisions. IT service providers are now extending data analytics services to connected devices, in order to capture relevant data that can be utilized for detecting patterns of interest and to accelerate processes in the future.

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Connected devices involve a number of sensors, and of different types, generating a variety of data in volumes. Often some sort of noise can enter the channel and corrupt the data. Moreover, data being generated is dynamic and highly unstructured in nature. Storing this data in a central storage space is not a solution, especially with rapidly increasing volumes of data being generated. Furthermore, transferring data generated from different devices to different storage space requires extra spending. These are some factors that have led to the introduction of edge analytics. Edge analytics for IoT devices, refers to capturing and analyzing data generated from a device without transferring it to a centralized storage space. Therefore, enterprises are utilizing the low cost computational power of devices for performing data analytics on them. IT companies are coming up with innovative ways to deal with the efficient data analytics methods, in order to serve a growing customer base with different needs and requirements from data. Therefore, factors such as need to capture and store only relevant data from the humongous amount of data being generated, reduce data latency in business processes, minimize the overall cost for data management and analytics are driving the growth of global IoT analytics market. Major restraints that global IoT analytics market faces are lack of skilled labor and the challenging task to develop data analytics services specific to businesses and customer’s needs.

IoT analytics market can be segmented on the basis of component, type of analytics, deployment model, phases, verticals, end users and regions. On the basis of component, the market can be segmented into software and services. The different types of IoT analytics are advanced object tracking, edge analytics, anomaly detection, crowd analytics and others. IoT analytics market can be segmented on the basis of deployment model into on-premises and cloud. On the basis of phases, it can be segmented into descriptive & diagnostic and predictive & prescriptive. The different verticals for IoT analytics are manufacturing, construction, retail, automotive, consumer electronics, and others. On the basis of end users, the market is segmented into large enterprises and SMEs. Region wise, the segmentation is done into North America, Latin America, Western Europe, Eastern Europe, Asia Pacific excluding Japan, Japan and Middle East and Africa.

North America IoT analytics market is expected to dominate in terms of value owing to high penetration rate of advanced technologies and presence of established players. However, Asia Pacific excluding Japan and Japan are expected to witness high growth rates as enterprises are introducing IoT in business strategies to improve productivity. Western Europe IoT analytics market is expected to witness a moderate growth rate followed by Eastern Europe IoT analytics market and Middle East and Africa IoT analytics market.

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Key players, such as IBM Corporation and Cisco Systems, Inc. among others in the global IoT analytics market focus on partnerships, mergers and acquisition and product innovations in order to deliver enhanced services to their clients and increase their customer base. For example, IBM Corporation and Cisco Systems, Inc. have entered into a partnership in order to collaborate IBM Corporation’s Watson IoT analytics on Cisco Systems Inc.’s edge devices. 

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