Abstract
The research presents the development of a Datamart (DM) with the objective of optimizing the generation of sales process reports through graphics, which are integrated into dashboards that allow the analysis of the indicators defined by the tourism agency URPI SUMAC Tours S.R.L, Peru. An adapted methodology was applied with different techniques and approaches based on the Ralph Kimball methodology. It developed a DM, favoring the construction of an OLAP cube for the organization under study, in order to build the graphs according to the indicators and these can be analyzed by the sales management and the administrative area. As a result, dynamic dashboards were obtained, which optimized the mechanisms for decision making in the sales area, having a broader and more reliable vision of the impact of tourism and thus shaping improvement objectives based on the results of the indicators. The sales area’s report delivery time improved by 85% and the sales management’s satisfaction rate improved by 90%. In the reports it was found that the sales for the four branches had a variability of no more than 1% among them.
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Chura, P.C., Yanavilca, A.V., Soria, J.J., Castillo, S.V. (2023). Datamart of Business Intelligence for the Sales Area of a Peruvian Tourism Company. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds) Data Science and Algorithms in Systems. CoMeSySo 2022. Lecture Notes in Networks and Systems, vol 597. Springer, Cham. https://doi.org/10.1007/978-3-031-21438-7_33
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