* Qlik Cloud* Qlik Automation* Qlik Data Transfer* Qlik Reporting* Sql* Python

Em parceria com a HYPERSCALE, prestei consultoria de BI para rede hoteleira Brisa. Atuei em todas as etapas do projeto, sendo elas: venda das licenças Qlik, levantamento de requisitos com os Key-Users, compreensão e mapeamento do Banco de Dados, transferências dos dados utilizando o Qlik Data Transfer, modelagem dos Data Marts e desenvolvimento dos dashboards.

Assumi o papel de líder em uma equipe de BI em dois projetos notáveis resultado da colaboração entre o NEES e o MEC (Ministério da Educação). Nesta função, fui encarregado de coordenar uma equipe multifuncional composta por DBA, analistas de dados e desenvolvedores. Nosso objetivo era transformar dados educacionais gerados pela plataforma integrada que foi desenvolvida em insights acionáveis, aprimorando assim a qualidade e eficiência da implantação da nova plataforma.

The project aims to implement Business Intelligence (BI) in various business areas of ASUS, in order to automate and improve internal processes. To make this happen, we are working on the entire workflow, from understanding the problem to displaying the results through the Qlik Sense platform. * Requirements Gathering * ETL * OLAP Cubes * Dashboard Creation * API-based Requests * SQL Server Database Creation * Docker

I have certification and authorization from HUAWEI to be an instructor for the Artificial Intelligence Training Course (HCIA-AI). In partnership with the EDGE Innovation Center, we have trained over 200 students in artificial intelligence, with 50 of these students passing the HCIA-AI exam. The instructor certificate covers the entire area of Python, Artificial Intelligence, TensorFlow, Machine Learning, and Deep Learning.

I participated as a research grantee in the project "1375 - Energy efficiency and mini-generation at UFAL," with my main activity being the real-time modeling of a photovoltaic generation system. During the project, I developed a recurrent neural network of the LSTM type, which predicts a five-second future horizon of the power generated by the solar panels. I used Python as the programming language and utilized libraries such as Keras and Scikit-learn.

I participated as a researcher in the project titled "Real-time implementation of an FPGA-based MPPT controller," where we developed the incremental conductance algorithm using the Verilog language and eventually implemented it on a programmable logic device FPGA.

The initiative was created in 2016 with the aim of establishing a model for human resource development, research, development, and innovation in the field of microelectronics in the country. The program was led by the EDGE Innovation Center, and during its implementation, various topics were studied, including Microelectronics, Digital Electronics, Digital Systems, FPGA, Verilog, and SystemVerilog. Activities related to project, implementation, and verification of digital hardware were also performed.