Prepare Datasets for Data Mining Analysis by Using Hortizontal Aggregation in SQL

Existing SQL aggregations have limitations to prepare data sets because they return one column per aggregated group. In general, a significant manual effort is required to build data sets, where a horizontal layout is required. The authors propose simple, yet powerful, methods to generate SQL code to return aggregated columns in a horizontal tabular layout, returning a set of numbers instead of one number per row. This new class of functions is called horizontal aggregations. Horizontal aggregations build data sets with a horizontal de-normalized layout (e.g. point-dimension, observation-variable, instance-feature), which is the standard layout required by most data mining algorithms.