As modern networks continue to expand in size and complexity, the potential for anomalous behavior has also increased--exponentially. Those anomalies can have a wide range of impacts on network performance, from minor performance disruptions to major breaches in #cybersecurity. Detection depends on #data, and that data is indeed “#Big.”
- Inefficient Data Ingestion
- Heavy Coding Burden
- Inaccurate Data Labeling
- Offline Model Tuning
Network data-scientists need new data modeling tools that can quickly synthesize copious amounts of network
data, sift through the noise, identify anomalous behavior, and implement effective corrective models
find out more about #AIStduio
click here download Data Modeling and Network Anomaly Detection Whitepaper
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