Moving from reactive to predictive maintenance requires the right tools for use by subject matter experts. As the power industry continues to advance from preventative to predictive maintenance, one ...

RVINE, Calif., Feb. 25 — Alteryx, Inc., the leader in self-service data analytics, today announced a new Predictive Analytics District in the Alteryx Analytics Gallery to make predictive analytics ...

The MTConnect standard enables manufacturing equipment to provide data for predictive analytics-which is a hot topic for good reason. The vision of anticipating breakdowns before they happen is ...

The promise of predictive analytics applications for B2B sales and marketing is to generate revenue by expanding existing markets and penetrating new markets. These predictive analytics applications ...

SAP is launching the application edition of the SAP Predictive Analytics software to help enterprises create and manage predictive machine learning models for applications that run business activities ...

Predictive Analytics - sometimes referred to as Predictive Data Mining - is a branch of Business Intelligence that attempts to use historical data to make predictions about future events. At its ...

Creative genius?: The integration of Tableau with Einstein Discovery, designed to bring predictive modeling and machine learning to a wider audience of business users, is the latest move to integrate ...

Statistical learning, the science of identifying patterns in data and using data to build models and make predictions, is receiving growing attention across industries. With the data science platform ...

BOSTON--(BUSINESS WIRE)--Rithmm, a cutting-edge, predictive-analytics sports betting application that empowers sports bettors to enhance performance through customized personal information algorithms, ...

The term “predictive analytics” is becoming increasingly familiar within the trucking industry as fleets look to make better use of the data collected by their back-office and onboard systems. Years ...

Although recent advances in computational capacity and machine learning have led to well-publicized breakthroughs in clinical risk stratification, these advances are noticeably absent in oncology. A ...