Digital Transformation in the fight against Coronavirus

COVID-19: An experience of the Comptroller General of the State of Goiás

Bruno Ferreira

PyPi PyPy Python Skills Python general R

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The Corona Virus - COVID-19 pandemic caused a significant impact on public services. In particular, it brought a massive digitalization of services that were offered in person. In addition, there was a great deal of pressure on official channels, whether to seek a service or to report a fact. Qualified and official information becomes an element in combating the pandemic. Knowing where to look for information, reporting a fact or getting a qualified response are essential steps to maximize the efficiency of the citizen's decision-making process, especially in a scenario of such uncertainty. The State has a fundamental role, whether as an inducer, executor or provider of the means necessary for information and decision-making to be effective at that time.
Connected by the growing demand, the State of Goiás, through the State's Comptroller General, published a series of technological tools with the objective of bringing information to the citizen, promoting social control and improving public policies to fight the Coronavirus.
This document seeks to show how technological tools were adopted and implemented in terms of transforming the ombudsman channels in the State of Goiás through the State's Comptroller General in actions to combat the Coronavirus pandemic. The document seeks to show how the transformation of the ombudsman channels occurred through machine learning techniques and data visualization.

Type: Talk (30 mins); Python level: Advanced; Domain level: Advanced

Bruno Ferreira

Graduated in Analysis and Systems Development - National Service of Commercial Learning - DF (2010), Postgraduate in Data Science, Master in Computer Science - Data Science from the University of Brasília and Master's in Economics from the University of Sorbonne.

Currently serves as parliamentary advisor and consultant in machine learning. In addition, he was a mentor at the University of Michigan in the area of ​​data visualization.

Has experience in Computer Science, focusing on data analysis