Business intelligence model powered by data science applied to enterprise resource planning

Currently, and due to various factors, the world has seen the need to implement digital media in its company. From a small company, where its employees must communicate by chat, to medium and large companies where they do remote work. However, this digitization is barely on the rise, so only relatively large companies have a digital management system for their companies. In many cases, small and medium-sized companies keep their data in excel sheets, which, beyond being good or bad, are functional in the vast majority of cases. However, these data are not useful during decision making. Today there are many software solutions that add value to this data, but companies fail to adapt to them. Either because of the cost of the software or because it requires an expert (programmer) for its configuration, or they are simply complicated to use. Enterprise Resource Planning (ERP) systems are software designed to maintain control within the company. These allow the monitoring of processes, inventory, production, among others, in an orderly and efficient manner. However, these software usually represent a great challenge for the technical team, since many of them have great restrictions, for example, a bad management of the user interface (UI), a bad user experience (UX), or a high complexity configuration, among others, for example SAP or Odoo. Additionally, these systems are usually expensive and require specialized technicians to operate. This means that very few companies manage to have an internal ERP system, and never manage to generate business intelligence (BI). The real value of the data obtained lies in the information that can be extracted from them, for example, a comparison of income/expenses, peaks and sales predictions, production reports, among others. It is understood as business intelligence, when the company is able to generate useful information for decision making. It is known as ETL (extract, transform, load) to the process of extracting and transforming the registered data, in order to obtain useful information. In the market there are several tools that allow us to generate these ETL, as well as KPI's or reports, for example Power BI or tableau; this project implements SQL sentences that extract the relevant information for Servigraf, thus making the most of the data generated by the company. This thesis aims to deliver a software capable of generating BI and achieving useful KPI's for Servigraf. To reach this goal, different modules have been established, such as: production, billing and reports. The production module manages production orders, inventory, materials. The billing module keeps a record of income, expenses and invoices. The reporting module generates the main Key performance indicators (KPIs). Both these KPIs and the reporting module are the key points of this software. The software developed is an ERP, which implements the basic functions of a production control system, a billing system, a customer management system (CRM), among other systems, and integrates them into a single software. On a technical level, the final software has a modular architecture, with the aim of being extensive and customizable. Additionally, a UI/UX layer is included, using the idea of components, with the aim of being as simple as possible for the end user. This ERP tool allows us to make decisions based on sales summaries, as well as establish KPIs that allow the company to meet objectives and modify strategies to achieve them, evaluating all the aspects involved.

• Autor principal: Altamirano López, Pedro Andrés (author)
• Format: bachelorThesis
• Idioma: eng
• Publicat: 2023
• Matèries: Enterprise Resource Planning (ERP); Data science; World Wide Web; Structured Query Language (SQL)
• Accés en línia: http://repositorio.yachaytech.edu.ec/handle/123456789/656