Predictive maintenance involves gathering targeted data for analysis, the results of which will help anticipate potential failures before they occur. Companies opt for this type of maintenance to avoid predictable incidents and repair equipment, assembly lines, or machinery with minimum impact on their operations. “Having to repair a faulty product is disastrous for a manufacturer’s brand image. But shutting down […]
Apache Spark is an open source cluster computing framework originally developed in 2009 at the AMPLab at University of California, Berkeley but was later donated in 2013 to the Apache Software Foundation where it remains today. Spark allows for quick analysis and model development, plus it provides access to the full data set thus avoiding the need to subsample, as often needed in environments like R.
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Learn more by downloading this Guide to Predictive Analytics.
In this new Guide to Predictive Analytics we will review how predictive analytics helps your organization predict with confidence what will happen next so that you can make smarter decisions and improve business outcomes. It is important to adopt a predictive analytics solution that meets the specific needs of different users and skill sets from beginners, to experienced analysts, to data scientists.