...DATA CURATION
Multifaceted
DATA
It’s been for quite a while now when basic information, like power utilization or temperature, can be sampled from devices to report the status of operation. It helps to account for critical elements of the ecosystem, yet it’s limited to basic visibility and not a deep knowledge of the environment.
Collecting all the data in the world won’t achieve your objectives without ability to draw detailed information of what and how this data can be used to support continuous operation – “noise” must be eliminated, references must be set and emphasis must be laid on identifying data that matters, thus feeding actionable processes with relevant information.
It’s said that, while collecting data from industrial devices, the large amount of it is incoherent, irrelevant and is practically useless. Besides overwhelming network with flawed information, it does create enormous challenges for real-time and predictive analysis.
Curating data at the edge resolves significant issues exposed by bandwidth and latency. However, it often involves algorithmic complexity that requires high-performing computing systems to process.
It’s been for quite a while now when basic information, like power utilization or temperature, can be sampled from devices to report the status of operation. It helps to account for critical elements of the ecosystem, yet it’s limited to basic visibility and not a deep knowledge of the environment.
Collecting all the data in the world won’t achieve your objectives without ability to draw detailed information of what and how this data can be used to support continuous operation – “noise” must be eliminated, references must be set and emphasis must be laid on identifying data that matters, thus feeding actionable processes with relevant information.
It’s said that, while collecting data from industrial devices, the large amount of it is incoherent, irrelevant and is practically useless. Besides overwhelming network with flawed information, it does create enormous challenges for real-time and predictive analysis.
Curating data at the edge resolves significant issues exposed by bandwidth and latency. However, it often involves algorithmic complexity that requires high-performing computing systems to process.
The vEDGE enables multifaceted data curation using innovative correlation algorithm and analysis to filter collected data while classifying its association with sensors, devices and functions. As the result, it: eliminates duplication of metadata whereas reducing frequency of transmission and size of collected data; contextualizes and aggregates relevant events yielding meaningful information to the outcome-based applications while tuning and optimizing performance of the end2end ecosystem.
...DATA CURATION
The vEDGE enables multifaceted data curation using innovative correlation algorithm and analysis to filter collected data while classifying its association with sensors, devices and functions.