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- Sales forecast in an IT company using time seriesPublication . Sobreiro, Pedro; Martinho, Domingos; Pratas, AntonioThe sales forecast is fundamental for the planning of the activity of the companies providing, important indicators for the support of the decisions of the managers. This study aims to explore the potential of time series prediction algorithms in an IT company. The forecast was based on the company's billing data for 192 months of activity. The analysis of the data was based on the Cross Industry Standard Process for Data Mining approach and for the treatment; we used the Anaconda IPython and Pandas. We developed the prediction with three models using R: Exponential Smoothing (Holt-Winters), autoregressive integrated moving average (ARIMA) and artificial neural networks (ANN). The comparison of the performance of each of the methods shows that the model based on artificial neural networks has a greater accuracy in the prediction. These results need deepening the study to broaden the universe of the studied contexts. However, the simplicity in the application of the artificial neural networks model makes possible its use in computer applications without specific knowledge, giving a reliable instrument that allows the supporting decision-making by managers.
- BUSINESS INTELLIGENCE IN THE TOOL MANAGEMENT USED BY THE CUT AND CNC MACHINES OF THE ORNAMENTAL ROCKS INDUSTRYPublication . Martinho, Domingos; TERESO, MARCO; Sobreiro, Pedro; Pratas, AntonioIn the ornamental stone industry, improving production processes is a constant challenge for managers looking for solutions that improve the competitiveness of the companies. The management of cutting and computerized cut command machine tools is one of the areas where this improvement in management processes can have a positive effect on the competitiveness and productivity of companies. With this purpose, a model based on business intelligence methodologies was developed to systematize and automate the management process. The proposed model consists of the following layers: acquisition, extract, transform and load, storage and access and analysis. The acquisition layer consists of the interface with data available in various formats. The extract, transform and load process aims to extract data from these repositories and load them into a data warehouse. While the access and analysis phase is based on the use of software tools with graphical user interface with advanced analysis reporting features. The technology infrastructure is supported by the open source Tibco Jaspersoft Community Edition software package, which provides tools for the practical implementation of the defined model. With this work, it is hoped to implement the defined business intelligence model thus giving answers to the problems identified by providing information for the decision-making that corresponds to the needs of the managers.