For modern businesses faced with increasing volumes and complexity of data, it’s no longer efficient or feasible to rely on analyzing data in BI dashboards. Traditional dashboards are great at providing business leaders with insights into what’s happened in the past, but what if they need actionable information in real time? What if they want to use their data to estimate what may happen in the future? Companies are taking notice.

When organizations track metrics by the thousands, millions, or even billions, it’s helpful in many ways to understand which metrics have close relationships, meaning when one metric behaves in a certain way, one or more additional metrics can be expected to behave in a similar or opposite way.

AI-based monitoring and anomaly detection is the key to ensuring that businesses can keep pace with the high level of service required for mission-critical applications. Early, contextual detection is a basic requirement for speedy resolution. AI-based monitoring creates more visibility and provides the agility needed to mitigate the outages, blackouts, glitches and issues that do and will happen.

According to a recent Capgemini research, fewer than half (48%) of consumers feel that the connectivity services that they have today adequately meet their remote needs. Still, many CSPs openly admit that they often hear about service issues via social media and sites like Downdetector. And with the fixed/mobile convergence, a negative home broadband experience now has the potential to cause churn for CSPs’ mobile customers too.