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A data analytics platform can monitor many devices to ensure that they are all working correctly. If an issue arises, an edge analytics platform may be able to rectify the situation autonomously.
FREMONT, CA: Edge analytics is a data gathering and analysis method involving an automatic analytical calculation on data at a sensor, network switch, or another device rather than waiting for the data to be relayed back to a centralized data storage.
Edge analytics has gained popularity as the Internet of Things (IoT) concept of connected devices has grown popularity. Streaming data from manufacturing machines, pipelines, industrial equipment, and other remote devices connected to the IoT creates an enormous flood of operational data in many firms, which can be difficult—and expensive—to handle.
Companies can set restrictions on what information is worth transferring to a cloud or on-premises data repository for later use by processing the data through an analytics algorithm as it is created at the edge of a corporate network. On connected devices, analyzing data as it is generated can help reduce latency in decision-making. For example, if sensor data from a production system indicates that a specific part is likely to break, business rules integrated into the analytics algorithm reading the data at the network edge can immediately shut down the machine and notify plant managers, allowing the part to be replaced.
Compared to sending data to a central location for processing and analysis, this can save time, potentially allowing enterprises to reduce or eliminate unplanned equipment downtime. Scalability is another significant advantage of edge analytics. Even as the number of connected devices deployed by enterprises—and the amount of data generated and gathered—grows, pushing analytics algorithms to sensors and network devices relieves the processing burden on enterprise data management and analytics systems.
What Are the Applications of Edge Analytics?
Monitoring edge devices is one of the most prominent use cases for edge analytics. This is especially true for Internet of Things (IoT) devices. A data analytics platform can monitor many devices to ensure that they are all working correctly. If an issue arises, an edge analytics platform may be able to rectify the situation autonomously. If automatic remediation is not possible, the platform may instead provide IT workers with actionable information to resolve the problem.