5G Networks unleash the Potential of Real-Time Data
DynamoEdge provides and end-to-end solution
for the digital lifecycle management of complex devices
Device-to-Cloud architectures now need to address the
Real-Time Quality of Experience
Mission-Critical IoT Applications
WINNING THE RACE OF REAL-TIME INTELLIGENCE
BY 2025, 30% OF THE WORLD DATA WILL NEED REAL-TIME PROCESSING
“Edge computing will inevitably join forces with streaming analytics to help communications service providers (CSPs) monetize their emerging 5G networks with the internet of things (IoT) and other real-time services.”
–Forbes, Jan 2021.”
1. LOW LATENCY
Edge computing embedded in 5G networks ensure that intensive processing can be carried out closer to equipment than with a typical cloud environment. Bandwidth hungry applications, such as time series analysis, can be conducted with only meta data transmitted immediately and full archives uploaded with less urgency.
2. ANALYZE BEFORE STORING
Reduces or eliminates network-induced delay for real-time applications, which rely on continual, fresh data insights to make automated updates and decisions. Further minimizing storage requirements by discarding unneeded data and storing analytics results only, reducing data telemetry transport costs.
3. STREAMING ANALYTICS
ML models are trained using historical data or data at rest. A lot of ML applications today aim to identify reliable, repeatable patterns and anomalies in historical data to identify what will happen in the future. The assumption here is that the world will stay the same and that patterns that were observed in the past will repeat in the future.. Rather than look at the past to deliver predictions, cutting-edge data science is focused on ‘querying the future” by looking at real-time data.