Getting Started with RapidMiner Studio
So here you are, a business analyst or developer or jack-of-all-trades. Things are going well, but it's time to fine-tune your business. You've probably collected a myriad of data points about your customer base and would like to determine which customers will remain loyal and which ones will likely churn. Attracting new customers comes at a price, so you'd really like to maintain your current customer base. How do you predict who may leave? What target audiences do you spend marketing dollars on to entice them to stay?
Using RapidMiner's modern enterprise platform, you can quickly and easily create analytic workflows called processes to determine who to target. In these processes you transform data by connecting the building blocks or operators that will eventually result in a model that helps predict the future. Sounds like fantasy or science fiction? It's not, it's predictive analytics reimagined. It allows you to operationalize predictive decisions closing the loop between insight and action.
This series of five Getting Started tutorials will help familiarize you with some basic features and functionality of RapidMiner Studio. Each tutorial describes and important component in the design process and each builds on the preceding tutorial. When you have finished the series you will have constructed a fully functional model that can be used as a starting point for real-world business use cases.
Below are some additional resources available to help you get up and running quickly with RapidMiner Studio.
|Part 1: Data Import||This document contains step by step instructions on how to set up your working environment and how to import a data set into RapidMiner Studio.|
|Part 2: Data Visualization||This document demonstrates how you can visualize the data to obtain greater insight.|
|Part 3: Creating a Model||This document demonstrates how to create a model to predict who is likely to churn.|
|Part 4: Applying the Model||This document demonstrates how to apply the model to a particular data set.|
|Part 5: Evaluating the Model||This document describes how to evaluate the performance of a model to ensure the best results.|
|Getting Started glossary||Contains quick descriptions of common RapidMiner Studio and data mining terms referenced in the above documents|
|User interface overview||RapidMiner Studio interface cheat sheet|
|Repository samples||Additional exercises for familiarizing yourself with RapidMiner Studio (once you have completed this tutorial)|