Solutions

Currently, engineers perform network optimization manually or using rule-based algorithms. As modern networks evolve and become more complex, these algorithms are quickly becoming obsolete or no longer viable.

The use of Machine Learning algorithms allows engineers to automatize their activities and to identify complex network issues that cannot be detected by humans or with traditional rule-based approaches.

Automatic anomaly detection and early warning on abnormal clusters are unique features that enhance the activities of a network engineer to a superior level of analysis.
Smart correlations between parameter settings and network performances pinpoint patterns and issues that were unknown until recently.
Automatic impact detection generated by changes in network performance provides instant feedback on optimization activities.

Monitoring and managing the configuration of a multi-vendor multi-technology network may look like a Herculean task. A complex mobile network can easily have more than 10,000 different parameters, multiplied by tens of thousands of cells.
Since 2006 Bwtech has been enabling Operators and Managed Service Providers to make this task easy, efficient and effective.
Operators can define their baseline rules and exceptions, then NetChart CM module will detect and enforce all inconsistencies automatically.
NetChart Configuration Management module is implemented in several tier-1 operators and has become part of their internal Network Assurance processes.