Analytics at the edge
You’ve no doubt come across Big Data Analytics but what are Edge Data Analytics? Seen as a quick win in terms of data resulting from IIOT (the Industrial Internet of Things), it means deploying advanced analytics solutions “at the edge” rather than at Enterprise level.
Essentially it’s about carrying out Big Data analysis closer to ‘the edge’ of the network, meaning nearer the machine that’s actually creating the data, and this ‘problem focused’ approach has a number of key business advantages:
- Equipment failure can be predicted in real time reducing downtime and improving maintenance scheduling
- Maintenance costs are reduced as equipment is maintained and repaired when necessary rather than via a fixed schedule of works
- Maintenance and repair operations crews are dispatched with appropriate training and expertise as the conditions will be known prior to dispatch
- More visibility on maintenance means spares inventories can be reduced, saving both money and space
- Larger number and more sophisticated array of sensors at the edge to deliver more reliable monitoring and greater insight to operations
- Optimized communications by reducing the bandwidth of data transmitted from the edge and lower costs of operation.
In this way Edge Analytics can be used to optimize uptime and maintenance for individual items of equipment.
CNIguard is already delivering Edge Data Analytics through its Sensorcore platform, which can also be supplied as a SaaS solution.
To find out more read about Edge Data Analytics and the business benefits, read Accenture Analytics’ full article here.
Most popular related searches
No comments were found for Analytics at the edge. Be the first to comment!