While automated machine learning (AutoML) is useful for operationalizing complex analytical tasks, market simulation...Read More
According to KDNuggets, the top 5 data science and machine learning methods for 2018/2019 are all statistical approaches. In addition, the top 5 did not change at all since 2017. ...Read More
This post was originally featured in Vol. 1, Issue 3 of the Rx Data News.Featured Interview: Greg Silverman, Founder and CEO of ConcentricBefore Concentric, Greg was Global Managing Director, Analytics and Valuation, for Interbrand. Greg received his BBA in Marketing and Retail from the University...Read More
Simulation is used when uncertainty of outcomes is high and when experimenting in the real world is costly. Both of these applications of simulation are helpful to scientists and researchers, but they come with a set of advantages and disadvantages. We have grouped these advantages and...Read More
Customer analytics is an expanding field as more and more data becomes available to organizations on what their consumers are buying, watching, reading, posting, and saying about brands, products, and services.
For many, the notion that you can recreate a virtual market that has a high predictive accuracy is fairly new.