Prepare Datasets for Data Mining Analysis by Using Hortizontal Aggregation in SQL
Source: Creative Commons
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.