Eduardo Amarante - Data Professional

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Eduardo Amarante

Data Professional

Welcome

#About me

Thanks for your interest! Allow me to share a brief overview of my IT career.

I'm Eduardo Amarante, and I work as a Data Analyst. My journey into the world of IT began during my PhD in Applied Geophysics, where I discovered my passion for technology. This realization led me to make a career change. In my most recent role, I had the privilege of working at Rede Bahia, the largest television company of northeastern in Brazil. My responsibilities included data cleaning, ETL processes, creating dashboards, web scraping, and setting up Data Warehouses, among other tasks. However, what truly drives me is using technology to address business challenges and provide essential support in the decision-making process.

I've acquired proficiency in various technologies to tackle a wide range of problems, such as Python, SQL, Power BI, and Django. In addition to these, I'm well-versed in Airflow, Astronomer, Airbyte, MongoDB, Dash, Linux, and Git.

This portfolio features projects categorized into Data Analytics, Data Engineering, Data Science, and Web Development.

Thank you for taking the time to read this, and feel free to connect with me. Cheers, Eduardo Amarante.

#Certifications

#Skills and technologies

  • airflow
    AirFlow
  • astronomer
    Astronomer
  • docker
    Docker
  • python
    Python
  • mySql
    MySQL
  • Postgree SQL
    Postgree SQL
  • dremio
    Dremio
  • html
    HTML
  • CSS
    CSS
  • powerBI
    PowerBI
  • Tableau
    Tableau
  • scikit learn
    Scikit Learn
  • Hadoop
    Hadoop

#Projects

  • Data Analysis - Emergency: 911 Call
    Technologies:
    Power BI Python
    Summary:
    This is a Business Intelligence project which was performed in Python and Power BI. This project aims to show some details of 911 emergency calls database in Montgomery County, PA.
    Click here to view the project.
  • Data Analysis - Financial Management
    Technologies:
    PowerBi Power Virtual Agents
    Summary:
    A synthetic dataset of fictitious company was used to develop a financial analysis such as costs and profit over time, financial KPIs and forecasting. In addition, a chatbot was created with Power Virtual Agents to give some support the dashboard user and make easier its usability.
    Click here to view the project.
  • Data Science - Default of Credit Card Clients
    Technologies:
    Python Machine Learning
    Summary:
    It is a machine learning project which goals was to predict default payment of credicards clients of Taiwan.
    Click here to view the project.
  • SQL Analytics with Dremio and Apache Hadoop
    Technologies:
    Dremio Apache Haddop Docker
    Summary:
    This project is a data archictect project using the Dremio to analyze data with SQL language. A Hadoop DataLake was set up to storage the datasets. The ratings dataset has over 20M of records.
    Click here to view the project.
  • ETL Process with Shell Script
    Technologies:
    Shell
    Summary:
    In this project, some part of data on website was extracted using only script shell. The results were recorded in a structured data file.
    Click here to view the project.
  • Full Stack Web Development
    Technologies:
    Django Python HTML CSS JavaScript
    Summary:
    I developed the website in Django Framework with my coworker in a full stack web development. The site runs in intranet of the company. In the documentation we have only a dummy data.
    Click here to view the project.
  • IaC: building infrastructure Docker with Shell Script
    Technologies:
    Shell
    Summary:
    I developed a script shell to build all infrastructure docker compound by 2 containers. In the first one I have Ubuntu with some packages installed in order to extract data from internet. In another we have a container with MySQL installed in order to storage the source data and set a Data Waherouse.
    Click here to view the project.
  • Queries Performance Comparison
    Technologies:
    Docker MySQL
    Summary:
    I created three queries that give the same result, but their performance are totally diferent. You can find out all scripts used in this project.
    Click here to view the project.
  • Supermarket Sales Analysis
    Technologies:
    Python Plotly DASH
    Summary:
    I analyzed supermarket sales data from the United States and presented the results through this dashboard. To facilitate future updates to this project, I developed it using the MVC architecture.
    Click here to view the dashboard.
  • Criminal Events Analysis from Vancouver
    Technologies:
    Python Plotly DASH
    Summary:
    I analyzed a criminal events data from Vancouver from 2012 to 2022. The dashboard contains three screens. In the home screeb is an introduction of the project, in overview analysis some metrics are displayed, and the user can make some analysis by period of day, neighbourhood, type of crime, and so forth. In the spatial analysis, it is possible to see the crime distribution along the Vancouver map. To facilitate future updates to this project, I developed it using the MVC architecture. The deployment of app was did on free tier of Render plataform, but it doesn't provide computational resources to run the ap properly. So, I recorded a video showing some features of my analysis.
    Click here to view the dashboard. Click here to download the video.

#Professional Experience

#Education

    October 2020

    Phd in Geophysics Applied

  • Universidade Federal da Bahia
  • March 2016 - October 2020

    June 2015

    Bach. in Geophysics

  • Universidade Federal da Bahia
  • March 2011 - June 2015

    May 2013

    Masters Degree in Geophysics

  • Universidade Federal da Bahia
  • August 2009 - May 2013

    October 2010

    Licenciate in Physics

  • Universidade Estadual de Feira de Santana
  • February 2005 - October 2010