The process mining is an umbrella term for a combination of data mining and process management techniques that use advanced algorithms, machine learning, and statistical methods to analyze organizations' data.

Process mining is a set of data-driven techniques for analyzing business processes using event data extracted from information systems such as enterprise resource planning (ERP) and customer relationship management (CRM). Process mining enables businesses to identify problems, rework, deviations in their processes and discover opportunities to optimize performance and maximize positive business outcomes.
Process mining applications allow business analysts and managers to:
Understand how business operations are performed by discovering “as-is” process diagrams based on event data from an IT system.
Analyze data to identify friction points in a business process and relate these friction points to key performance indicators.
Understand what contributes to favorable and unfavorable process outcomes, for example, different activities that contribute to orders that are delivered on time versus orders that are delivered late.
Predict the future performance of a process under various scenarios so teams can make better decisions and better prioritize process automation and process improvement efforts.