This series is all about combining two completely different technologies that target two completely different audiences. However, it turns out that those two audiences often have to serve the same master in looking for information and insight within their data. And typically those two audiences don’t or can’t talk to each other, which makes driving common goals a bit difficult.
PowerPivot is a tool for preparing and creating data applications from a business analyst’s perspective. You can bring data in from multiple sources, match them together, derive new information, create some calculations, and present the results in an attractive and meaningful business context. You can download and find more information about PowerPivot at www.powerpivot.com. Go ahead – it’s free!
R is a statistical language for preparing and creating data applications from a data scientist’s perspective. You can import data, apply statistical tests and analysis, derive new information, and visualize the results in a scientific and statistical context. You can download and find more information about R from www.r-project.org. Go ahead – it’s free!
So the question remains, how can we make these two worlds collide in a meaningful way that takes the science performed in R and applies it to the business context of PowerPivot. You knew I was going to say this, but Predixion Insight is the way! Predixion Insight and Predixion Insight for Excel allows you to take predictive models created in R and apply them to data in PowerPivot (and Excel actually), thereby taking the scientific abstracts and providing them concrete business context.
In this three part series, I’m going to walk through the complete process of creating a model in R and then applying it to data in PowerPivot by means of Predixion Insight. The four parts will cover the following topics:
- Part 1 – Intro (you’re reading this now)
- Part 2 – Creating a classification model in R
- Part 3 – Evaluating and Scoring R models in Predixion