The Philosophy of MiningMart
In this help-topic you will learn about the basic ideas behind MiningMart. Its different components and the way they interact will be explained. Basic notions that will be needed for any MiningMart session are presented. This will also help you to understand the whole help and any other documents related to MiningMart. MiningMart is a system that supports the development, documentation and re-use of results in knowledge discovery. It is assumed that you are familiar with general concepts in Knowledge Discovery (Data Mining). However, we give a few informal definitions here to provide a common understanding.

The Knowledge Discovery Process refers to the technical steps of data acquisition, data cleaning, data preparation as well as data mining and model testing.
Data Mining is the step in the knowledge discovery process where a Machine Learning algorithm is applied to learn a model which is used to make predictions on new data.
Preprocessing comprises all steps that are undertaken in order to bring the data into a format that is accessible for data mining. The result of preprocessing is the input for data mining without any further modifications. The input for preprocessing is the data as it is stored in a data warehouse or even the operational database of an institution.

Subtopic The MiningMart Approach gives an overview of the MiningMart approach to the knowledge discovery process. In the next subtopic basic terms that are used in MiningMart are defined and explained. Those terms will be used everywhere in the MiningMart system and documentation, so it is a good idea to familiarize yourself with them.
The MiningMart Approach
Basic Notions of MiningMart