Why Anomaly Detection?
A Telecom operator must monitor the Network health through various metrics to gauge the performance of various services offered. The Autonomous Detection of any abnormality in the behaviour of metrics and flagging it out can be called as Network Anomaly Detection.
Key Metrics or KPIs of any Networking company will exist in different data streams. Some AI/ML methods can be used to understand the Business behaviour of the Metrics. Learning from the historical data, the algorithms can point out any anomalies existing in the data. There are some tools which can help any Network Operator to do the Anomaly Detection for them seamlessly.
Benefits of a Network Anomaly Detection Tool:
A Network Anomaly Detection tool can add value to you in the following ways:
- Connect to all the different Data Sources where the metrics are generated.
- Use Proprietary unsupervised algorithms which are created for understanding and learn all the trend, periodicity and seasonality in the data.
- In Real-time, it can identify all emerging issues autonomously which deviates from the normal behaviour
- Various anomalies can be grouped using correlation which will be useful for doing root cause analysis in case of any incident.
- Provide Smart insights which can be consumed by the Business users without any dependency on Data Analysts.
- Reducing significant efforts in configuration and development efforts so that the Network Company can focus on the results and take meaningful decisions.
An Anomaly Detection tool such as CrunchMetrics can track the Call Setup Success Rate, Average Data Network Quality and more, across multiple regions, operators, devices and Cell sites. Once it finds any anomalies (abnormality in data behaviour), it sends out alerts to respective stakeholders so that they can take corrective actions if required.
An Anomaly can be incidents as well as Business opportunities. So, you can use the tool for mining all incidents and also check if there are any Business opportunities which you can take advantage of such as a surge in a particular service offering, You can learn from the Customer behaviour and build bundle packages or other offerings based on the information.
Summon the power of Augmented Analytics to help you identify risks and business incidents in real-time.
Kshitish Sahoo is the product manager at CrunchMetrics. He has more than 7 years of experience in domains such as Energy and Utilities, QSR, Healthcare, CPG, Real Estate, Banking and Insurance and E-Commerce. He has worked on setting the strategy, developing the feature propositions, marketing the product and handling the financial metrics of the product.