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ANOMALIES MANAGEMENT SOLUTION

Improve the awareness and understanding of network performance deviations

CSPs face challenges in swiftly detecting anomalies while minimizing false positives. Identifying root causes within a dynamic network, integrating diverse data, and ensuring scalability present complexities. 

CHALLENGES

Managing the immense volume and complexity of network data poses difficulties. Analyzing diverse data sources for anomalies requires sophisticated tools and algorithms

Data volume and complexity

Minimizing false positives is crucial. Overly sensitive anomaly detection systems can generate unnecessary alerts, leading to resource wastage and decreased efficiency.

False positives

Navigating the ever-changing landscape of network environments poses a continual challenge. Alterations in network configurations and traffic patterns have the potential to affect the accuracy of anomaly detection.

Dynamic network traffic patterns

Unifying data from varied sources, including performance metrics, logs, and user behavior, into an anomaly detection system necessitates meticulous coordination.

Integration of Data Sources

Pinpointing the root cause of anomalies is intricate. Multiple interconnected network elements make it challenging to trace issues back to their origin accurately.

Multi-domain root-cause identification

Using a single tool for network anomaly understanding is challenging due to the diverse data types in networks. Different tools are often required for comprehensive analysis and accurate insights.

Multiple tools needed

Kenmei's Anomalies Management solution enables CSPs to detect network deviations and gain insights into their root causes, enhancing awareness and facilitating proactive issue resolution.

VALUE PROPOSITION

Multi-data source integration in one single tool with Root Cause Analysis.

ONE SINGLE TOOL

The Root Cause Analysis algorithm identifies the network deviation reason.

ROOT CAUSE ANALYSIS

The solution automatically identifies the clusters with similar patterns.

AUTOMATIC CLUSTER ANALYSIS

The solution integrates Alarms, Work Orders, Counters, Topology, Parameters, Inventory, Open Data, etc.

MULTI-DOMAIN DATA INTEGRATION

Automated anomaly detection and root cause analysis enhance overall network performance by swiftly identifying issues, minimizing downtime, improving efficiency, and ensuring a reliable and secure network environment.

BENEFITS

Accelerates resolution time by utilizing automatic correlation of data sources and efficient root cause analysis.

Accelerate Mean Time to Resolution

x3

​​Engineers now spend fewer hours on the comprehensive analysis of network performance deviations compared to previous practices.

Engineering hours reduction

+90%

Be mindful of anomalies, understanding their influence on cluster areas.

Analyze the impact on clusters rather than individual cells

x2

The solution incorporates multiple rules to alert you to previously unrecognized issues.

Enhance awareness of overlooked issues

x1.5

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