rissa2019 / airbnb

Airbnb SQL Final

This is the final project for SQL class.

Intro

The data on Airbnb listings, reviews, and calendar details for Berlin was scraped on November 7, 2018 and created by Murray Cox (Battendorf, 2019). It contained 22,552 listings and the attributes were distributed across six datasets.

Our proposal to Airbnb Berlin was to provide a database structure that would allow them to find a more accurate and standardized way of predicting the rental price for each neighborhood based on listing descriptions. Similarly, our design was made with the goal of identifying the busiest times of the year to visit Berlin as well as the dollar amount in price spikes during the busy seasons. Finally, given its strong interest in customer satisfaction, we wanted our database to be able to provide information to identify trends in reviews of Airbnbs users. This could potentially provide suggestions to the managerial team that could lead to respective trainings or feedback so that hosts can work on better ways to attract more customers.

Files

For Inital data cleaning of source datasets using R code: data_cleaning.r

ETL Process using R code: ETL_process.r

10 analytical procedures using SQL : analytical_procedure.sql

10 analytical procedures using R : Analytical_Procedures.r