Desenvolupament d'un sistema de suport a la presa de decisions a la direcció d'IThinkUPC amb intel·ligència artificial

This project is an example of the need of modernization and upgrade of actual systems towards a new system with new advantages and innovative data models.Thus following the new trend that database management is heading. The main objective is to upgrade the actual system to a more clean and easy-on-use one. The actual system the company IThinkUPC uses is a database with all the information of the contracts of clients and dedication of the empoyees are mixed and a visual component for the financial team that have to elaborate the reports with it. The main objective will be to create a well organized databse and a new visual component within the companys needs. The working methodology followed has been a Kanban panel approach to organize the tasks, assigning them with the collaborative Asana tool. The project¿s development will follow four clearly different stages: 1. A first stage where we will analyze the state of the art, from the initial data loading to the final visualization platform. 2. A second stage where we will be taking the needs and demands of the client to develop the different proposals and alternatives of the data model. 3. A third stage where the work will be focused on the data extraction, transformation and load based on the chosen data model. 4. A final fourth stage where the efforts will be on the final visual elements that the client expects. In order to execute this project, different technologies will be used. These technologies are one of the most used and better user rated on the market. Despite not being the newest ones, they are the ones the company is most familiar to them and have proven better results. Regarding the data management and storage, PostgreSQL is the chosen software that will be used due to its global use and estandaritzation. We also use it because we seek to have a better response and load time. For the extraction, transformation and load of the data, we will use Hitachi¿s Pentaho Data integration, also known as ¿Kettle¿. We