The Cross-Industry Standard Process for Data Mining, better known as CRISP-DM, has been around for more than a decade, and it’s by far the most widely-used analytics process standard.It’s an ...

Process mining helps organizations gather insightful data to evaluate the reliability, efficiency and productivity of business processes throughout the company. Topics IT Operations ...

Data mining is a process that turns large volumes of raw data into actionable intelligence. Data mining uses statistics and artificial intelligence to look for trends and anomalies in data. It's ...

The data mining process is usually broken into the following steps. Step 1: Understand the Business . Before any data is touched, extracted, cleaned, or analyzed, ...

This is the age of the internet. As William Gibson’s haunting imagination of cyberspace comes to insipid life, we are blown into the new era of virtual networking, learning and earning.

Data mining process. The Cross Industry Standard Process for Data Mining (CRISP-DM) is a six-step process model that was published in 1999 to standardize data mining processes across industries.

Lucas M. Schroth and Urszula Jessen founded Process.Science to address inefficiencies in traditional data analysis. The company utilizes an AI-powered process mining platform that integrates ...

London-based data mining expert Tom Khabaza offers some help, in the form of a simple way to explain important analytics concepts. His “9 Laws of Data Mining” are widely accepted in the ...

The technology — in this case, provided by Celonis, the first time a U.S. state has used its process mining tools — uses specialized algorithms that analyze data so users can better understand ...