Abstract-Data mining is the field which has effectiveness in real world scenarios. Data sets are prepared from accepted transactional databases for the purpose of data mining. A vast amount of time is needed for creating the dataset for the data mining analysis because data mining developers required to write multifaceted SQL queries and many tables are to be coupled to get the aggregated result. Here, we recommended simple, however powerful, techniques to generate SQL code to formulate aggregated columns in a very horizontal tabular page layout, getting a few numbers as opposed to one variety per short period. This new functions class is named horizontal aggregations. Data sets are build using horizontal aggregations with a horizontal de-normalized layout (e.g., observation-variable, point dimension, instance-feature) which is the standard layout required by most data mining algorithms. Building user-defined new aggregate function that aggregate numeric expressions and transpose results to produce a data set with a horizontal layout is focused in this paper. Horizontal aggregations represent an ex-tended form of traditional SQL aggregations in which it returns a set of values in a horizontal layout. It is a new class of aggregations that have similar behavior to SQL standard aggregations which produces tables with a horizontal layout. As compare to standard SQL aggregations we call it vertical aggregations since they produce tables with a vertical layout. In Horizontal aggregations just require a small syntax extension to aggregate functions called in a SELECT statement. In other words, horizontal aggregations can be used to generate SQL code from a data mining tool to build data sets for data mining analysis.