This notebook validates and extends the data engineering workflow for our team’s Data 607 Project 3. It processes the original Google Trends dataset (data_science_skills_gt.csv) into a clean, long-format version (trends_long.csv) and stores it in a structured SQLite database (warehouse.db). The project demonstrates reproducible data cleaning, transformation, and database loading in R, ensuring team members can reliably access the processed data for analysis and visualization. The process highlights best practices for collaborative version control and R-to-SQL integration in data science workflows.

Prueba

Clase 3 del curso de Matemática Actuarial II de la Maestría en Ciencias Actuariales Aplicadas de la Escuela de Educación Continua de la Universidad Galileo. Guatemala.

Biostatic_Assignment_2

Workshop 2 Solution - Algorithms and Data Analysis Alberto Dorantes, Ph.D.