This website, developed by Dr. Saed Sayad, includes a detailed classification of data mining methods. Data mining is explained in terms of six stages: Problem Definition > Data Preparation > Data Exploration > Modeling > Evaluation > Deployment.
"Data preparation is about constructing a dataset from one or more data sources to be used for exploration and modeling. It is a solid practice to start with an initial dataset to get familiar with the data, to discover first insights into the data and have a good understanding of any possible data quality issues. Data preparation is often a time consuming process and heavily prone to errors. The old saying "garbage-in-garbage-out" is particularly applicable to those data mining projects where data gathered with many invalid, out-of-range and missing values. Analyzing data that has not been carefully screened for such problems can produce highly misleading results. Then, the success of data mining projects heavily depends on the quality of the prepared data." (Sayad, 2014)
- Problem Definition
- Data Preparation
- Data Exploration