ARCHIVE

Many companies have tried to feed business data, such as business activity, into IT or APM monitoring solutions, only to discover the data is too dynamic for static thresholds. Some companies choose to depend on analyze BI dashboards to find issues, but that leaves anomaly detection to chance. As companies have tried to solve these challenges, AI is driving a future where monitoring business data is monitored autonomously.

Why? Because monitoring machines and monitoring business KPIs are completely different tasks.

AI and machine learning is expected to create the biggest wave of disruption in analytics, from data integration to anomaly detection and forecasting. Businesses must evaluate which areas of their data infrastructure stand to benefit and which technologies are best suited to their needs.

Continuous, accurate measurement of your primary KPIs is only half of the battle. The other half is turning all that data into actionable insights. Self-service BI is making it easier than ever.

Data analysts end up spending a lot of time investigating issues that are hidden within the vast volume of data and events, and often don’t know what to look for.

Should data analysts and other "knowledge sector" employees feel threatened by AI? Here's what industry experts have to say on the subject.