Enterprise applications for big data continues to gain momentum across the globe. Moreover, cognitive computing and cloud technologies are making it much easier to extract valuable insights from vast amounts of stored data. That insight is a key component of successful digital transformation projects.
The Internet of Things (IoT) analytics market is rapidly expanding from the cloud to the edge of the network as advances in compute capabilities -- and the lower cost of communications hardware -- unlock new opportunities to apply analytics closer to the thing where data is generated or collected.
According to the latest worldwide market study by ABI Research, the volume of data captured by IoT-connected devices will grow nearly six-fold over the forecast period and reach 2,000 exabytes (2.0 zettabytes) in 2021.
IoT Data Analytics Market Development
Today, only a fraction of captured data is recorded at the endpoint for further processing or storage. The goal with edge analytics is to make better use of captured data to reduce critical issues in real-time and to improve predictive and prescriptive analytics models in the cloud.
"In the early days of IoT, the focus was on the connectivity of the devices rather than their intelligence," said Ryan Martin, senior analyst at ABI Research. "With edge analytics, organizations have access to a more granular degree of insight-generating data, which facilitates a system-level approach to improve operations and create new services."
Analytics produced at the edge -- and in the cloud -- offer value across the enterprise, as well as the supply chain, from product operations to OEM suppliers to R&D.
Companies such as Cisco, Dell, Intel, PTC, and Predixion Software (acquired by Greenwave Systems) deploy intelligence in IoT systems at three levels. The first level is the deepest and refers to endpoint devices capable of processing the information they gather.
The second level covers gateway devices that aggregate traffic and deliver commands to and from the endpoints. The third, or highest, level concerns the cloud or enterprise infrastructure to which the endpoints and/or gateways transmit data over a backhaul connection.
Outlook for IoT Analytics Growth
"Whether the intelligence of IoT systems and subsystems should reside at the cloud or at the edge is one of the most critical questions in the industry," concludes Martin.
The heterogeneity of machines, sensors, and connected equipment necessitates that various actors and their analytics solutions work in harmony to maximize business value.
The Internet of Things (IoT) analytics market is rapidly expanding from the cloud to the edge of the network as advances in compute capabilities -- and the lower cost of communications hardware -- unlock new opportunities to apply analytics closer to the thing where data is generated or collected.
According to the latest worldwide market study by ABI Research, the volume of data captured by IoT-connected devices will grow nearly six-fold over the forecast period and reach 2,000 exabytes (2.0 zettabytes) in 2021.
IoT Data Analytics Market Development
Today, only a fraction of captured data is recorded at the endpoint for further processing or storage. The goal with edge analytics is to make better use of captured data to reduce critical issues in real-time and to improve predictive and prescriptive analytics models in the cloud.
"In the early days of IoT, the focus was on the connectivity of the devices rather than their intelligence," said Ryan Martin, senior analyst at ABI Research. "With edge analytics, organizations have access to a more granular degree of insight-generating data, which facilitates a system-level approach to improve operations and create new services."
Analytics produced at the edge -- and in the cloud -- offer value across the enterprise, as well as the supply chain, from product operations to OEM suppliers to R&D.
Companies such as Cisco, Dell, Intel, PTC, and Predixion Software (acquired by Greenwave Systems) deploy intelligence in IoT systems at three levels. The first level is the deepest and refers to endpoint devices capable of processing the information they gather.
The second level covers gateway devices that aggregate traffic and deliver commands to and from the endpoints. The third, or highest, level concerns the cloud or enterprise infrastructure to which the endpoints and/or gateways transmit data over a backhaul connection.
Outlook for IoT Analytics Growth
"Whether the intelligence of IoT systems and subsystems should reside at the cloud or at the edge is one of the most critical questions in the industry," concludes Martin.
The heterogeneity of machines, sensors, and connected equipment necessitates that various actors and their analytics solutions work in harmony to maximize business value.