A telecom company (Vodafone), had the need to implement a Business Intelligence solution for
Roaming data across a wide set of different data sources. Based on the data visualization of this
solution, its key users with decision power, can make a business analysis and needs of infrastructure
and software expansion. This document aims to expose the scientific papers produced with the various
stages of production of the solution (state of the art, architecture design and implementation results),
this Business Intelligence solution was designed and implemented with OLAP methodologies and
technologies in a Data Warehouse composed of Data Marts arranged in constellation, the visualization
layer was custom made in JavaScript (VueJS). As a base for the results a questionnaire was created to
be filled in by the key users of the solution. Based on this questionnaire it was possible to ascertain
that user acceptance was satisfactory. The proposed objectives for the implementation of the BI
solution with all the requirements was achieved with the infrastructure itself created from scratch in
Kubernetes. This BI platform can be expanded using column storage databases created specifically
with OLAP workloads in mind, removing the need for an OLAP cube layer. Based on Machine
Learning algorithms, the platform will be able to perform the predictions needed to make decisions
about Vodafone's Roaming infrastructure
