Implementación de un Data Mart Financiero y Presupuestario Usando Base de Datos en Memoria

Abstract

In business intelligence (BI) systems, users perform queries in star schemas, but although their performance is better than in relational structures, they require a lot of processing time to update the data; The greater the volume of data, the more degradation occurs in the performance of queries, which affects the financial and budgetary process for timely decision making. The access to data in memory is faster than reading them on a hard disk, so the proposed solution is to implement a data mart that uses a database in memory. The solution was applied to a case study in a PYME (Small and Medium Company) improving the time of generation of financial and budgetary reports for timely decision making