Programação de um módulo de business intelligence no Block-Based Integrated Platform for Embedded Systems (BIPES)
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Universidade Federal de São Carlos
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With the modernization of technologies and the activities of the society, the decision-making process starts to depend on the analysis of increasingly larger data sets. The increase in the use of the internet, the emergence of the Internet of Things and the popularization of Big Data, affect in a expressive way, the increase in the generation of high volumes of data with greater variety at high speed.This lead the demand for more complex tools that allow companies to become more Data Driven, which means to have their processes, decision-making and strategic planning based on data. In this context Business Intelligence tools emerged, being able to organize and delivery well-structured ways to manipulate, analyse and visualize those data. The Block-based Integrated Platform for Embedded Systems (BIPES) is a platform that allows the no-code development for embedded systems, empowering users to develop solutions using programming blocks. Most solutions developed using BIPES are related to sensor data collection, and so far, the platform offer tools for real-time analysis of the data, however it does not offer a way to analyze large volumes of historical data. BIPES users, in a visual and easy way, cannot extract insights and make decisions that impact all the scope of the project. Thus, this present work proposes to develop, using BI tools, a module capable of assisting in the analysis of sensor data and the decision-making processs, which can be integrated with the BIPES. For this purpose , a dashboard was developed using the Tableau Desktop tool, capable of present the historical behavior and forecasting, device performance ranking, nonconformity alert, behavior throughout the day, outilers presence, and indicators of daily average and total results.
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PACHECO, João Victor. Programação de um módulo de business intelligence no Block-Based Integrated Platform for Embedded Systems (BIPES). 2022. Trabalho de Conclusão de Curso (Graduação em Engenharia de Computação) – Universidade Federal de São Carlos, São Carlos, 2022. Disponível em: https://repositorio.ufscar.br/handle/20.500.14289/16662.
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