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Data Engineering & Analysis Case

Importing & Analyzing the Brazilian Vehicle Fleet

Text sanitization pipelines, batch loading of government data, and hybrid modeling for high-performance analytical queries.

🐍 Python / Pandas 🗄️ SQL (MySQL / Postgres) 🍃 MongoDB Document Store ⚡ Data Cleansing & Fuzzy Match
01 Understanding the Data 02 Importing the Data 03 FIPE Data 04 Classification 05 Dashboards
Overview of the structure of files and data of the Brazilian vehicle fleet

Analysis of the Brazilian Fleet

Have we forgotten that impactful phrase “data is the new oil”? Everyone talks about artificial intelligence, but the most important thing is to generate impact and results. To do that, it is necessary to know how to analyze information.

My intention is to analyze the evolution of the vehicle fleet in Brazil over the years and how the brands performed. The project is still in progress and will be presented in stages.

General plan

  1. Study the data made available by the open data portal of the SENATRAN / Ministry of Transport.
  2. Import the data in Access and CSV format.
  3. Import the FIPE data made available on Kaggle.
  4. Classify the SENATRAN data according to the FIPE data.
  5. Explore the dashboards.

I hope this content is useful to those who are starting to work with data and serves as inspiration for those who already work with data but have not yet had time to explore Brazil’s government data.

Access the first stage of the study.

Access the second stage on data import.

Access the stage on FIPE data.

Access the classification and enrichment stage.

Access the dashboard exploration stage.