An Horizontal Aggregation Approach for Preparation of Data Sets in Data Mining

In Data Mining, Preparing a data set for analysis is generally the most time consuming task, it requires many complex SQL queries, joining tables and aggregating columns. 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 l 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 aggrega data sets with a horizontal denormalized layout, which is the standard layout required by most data mining algorithms.