Network analytics tools continuously gather data from various sources, including routers, switches, access points, and servers. This data is then processed using AI and ML algorithms to detect patterns, identify anomalies, and predict potential issues.

Key functionalities include:

• Traffic Analysis: Monitors data flow across networks to identify congestion and optimize bandwidth usage.
• Anomaly Detection: Recognizes unusual activities that may indicate security threats or performance issues.
• Predictive Analytics: Uses historical data to anticipate network failures or capacity needs.
• User Behavior Insights: Examines how users interact with the network, aiding in policy creation and optimization.
• Automated Network Management: Enables self-healing networks by automatically resolving detected issues.

Use Cases of Network Analytics

Network analytics is widely used across various industries to maintain high-performing, secure networks. Common applications include:

• Enterprise IT Management: Ensures reliable connectivity and security across corporate networks.
• Telecommunications: Helps service providers monitor network health and enhance customer experience.
• Retail & Hospitality: Enhances guest Wi-Fi performance and provides insights into customer behavior.
• Smart Cities: Supports IoT-based infrastructure by analyzing sensor data and optimizing connectivity.
• Healthcare: Ensures secure and uninterrupted connectivity for critical medical applications and devices.