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Posted
AuthorRyan Harrington

by Dr. Steve Poulin

Over the past several years, artificial intelligence (AI) has received an increasing amount of attention (and scrutiny) recently because of the exciting new ways it is being used.  Many people are familiar with the technologies that AI has enabled, but how many people actually know how it works?  In this post, we'll explore what makes artificial intelligence...artificial intelligence.

Posted
AuthorRyan Harrington

by Dr. Steve Poulin

Those who are working with Predictive Analytics are always trying to find a better more effective way. We have chosen a field that that can get better and better every day. And in the last few years, with the development of new technologies and approaches to acquiring data – we are finding the spotlight on us to do just that: find better ways. Traditionally, there are three primary ways to develop models and algorithms for predictive analytics: (1) the expensive SAS solution, (2) the cheaper but just as effective IBM SPSS, or (3) the open source “R”. We, at CompassRed, think there is a fourth: Leverage the best of all.

Posted
AuthorPatrick Callahan

by Steve Poulin and Patrick Callahan

As a Data and Analytics company, we at CompassRed have seen the full cycle of leveraging data for insight with each phase of development being just as important as any other. Deployment is the part of the predictive analytics process that puts the predictions to work.  Predictive analytics requires a very time-consuming process of data preparation and a very complex process of finding the best algorithms (also known as “modeling”) for producing predictions.  However, all of this effort is for naught if the predictions are not used by an organization to meet their objectives, which typically means increasing revenue and decreasing costs

Posted
AuthorPatrick Callahan