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Cisco and SAS found that organizations were spending too much time figuring out how to leverage IoT data instead of focusing on the data itself. The Cisco SAS Edge-to-Enterprise IoT Analytics Platform aims to eliminate the time organizations spend analyzing the data, allowing them to use the data almost as soon as it’s collected.
"When you dig down into the heart of the IoT discussion, it's all about the business value potential presented by bringing IT and OT together – a complex challenge our members are eager to solve,” MESA International President Mike Yost said in a statement. “Confidently pushing analytics through the network to where the data is created solves many problems. I trust people will enjoy being transformed from data caretakers to explorers, discovering all the possibilities that exist with better insight."
Cisco and SAS developed this tool in response to the significant adoption of IoT devices and strategies across all major industries.
Organizations are deploying connected devices that constantly collect data that can be impossible to sort through without the correct tools. For healthcare organizations in particular, this data has the potential to give insight into long term patient health based on personal data collected by patient devices.
"The value of IoT lies in the data that it provides," IDC Research Director Alan Webber said in a statement. "But data by itself is not valuable until, using analytics and analysis, it can be turned into information, knowledge and action.
“That is what makes this partnership between SAS and Cisco so exciting. It brings two world-class companies together to offer truly edge-to-enterprise value in transforming edge data gathered through IoT into unmatched business value through analytics."
The Cisco SAS Edge-to-Enterprise IoT Analytics Platform is made up of several key features including edge computing, flexible enterprise computing, and management.
The solution can run against data-in-motion with near real-time response times with edge computing. Edge computing allows analytics to be generated close to the IoT devices creating the data, sorting the data based on its content and value.
The solution also uses edge computing to give organizations analyzed data quickly so they can make decisions quicker.
Flexible enterprise computing identifies relevant data sets at the edge and transports them to the datacenter. The data is then combined with related data in the datacenter to give it context and analytics techniques such as visualization, machine learning, and data mining can be applied.
The data can either be stored in the datacenter for future use, or deployed back to the edge.
The new technology also features a management solution that connects the on-premise datacenter or cloud to the edge and supports management of analytics on different network layers.
By allowing analytics to take place close to the source of the data, healthcare organizations are able to utilize generated results much faster than if the data was simply transported to the datacenter to be analyzed. Clinicians can get more accurate results while they are treating a patient, giving them better insight into patient care.
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