Extract, Transform, and Load the Data (ETL) Mini Project

Clean two different sources, and join those two datasets together. Then, we load into the database to be able to run queries in the SQL database.

Compare and Contrast the two data about the relationship between diseases and hospital beds.

First Data Source : "Health Status Of 26 Of The Nation's Largest And Most Urban Cities"

• Source: https://data.world/health/big-cities-health

This dataset illustrates health status of 26 of the nation’s largest and most urban cities as captured by 34 health (and six demographics-related) indicators. These indicators represent some of the leading causes of morbidity and mortality in the United States and leading priorities of national, state, and local health agencies. Public health data were captured in nine overarching categories: HIV/AIDS, cancer, nutrition/physical activity/obesity, food safety, infectious disease, maternal and child health, tobacco, injury/violence, and behavioral health/substance abuse.

First Data Source : "Hospital Beds Per 1,000 Population By Ownership Type"

• Source: https://www.kff.org/other/state-indicator/beds-by-ownership/

In this dataset, it discusses about staffed beds for community hospitals, which represent 85% of all hospitals in each states in the US. Figures may not sum to totals due to rounding.