• Sourcing deals for rental property investing can be a challenging process. Not only does extensive searching need to be done but deal analysis must be thorough in order to determine whether a property can be cash flow positive. This app serves as a tool which queries a real estate listing site and loads data into a data warehouse. Thereafter, the data is served along with user-defined master data in order to present useful functionalities for investors such as summary market statistics, a geocoded plot of property locations, lead generator, and investment deal calculator. I used a realestate.com.au Python wrapper designed by GitHub user Tom Quirk to assist with the source ETL process.

• High-level design and data flow:

  

• Dashboard:
  View Australian property market stats as according to listings on realestate.com.au and drill-down by state.

  

• Map:
  View current listings in data warehouse fact table. Hover over a listing to view the precise address.

  

• Leads:
  Based on user-defined master data, e.g. downpayment percent, loan interest rate, and desired ROI, current fact data is displayed with a calculated column of whether the property would make sense as deal based on your numbers (‘Buy’ or ‘Pass’).

  

• Calculator:
  Quickly try out different scenarios based on your investment strategy. Take screenshots of your results.

  

• Down the line, I plan to expand this project to add more functionality and package it for public use.

Versions used:

• Python 3.10.4
• R 4.2.0

View the project on Github:
David-dmh/dw-rei

• Python
• R
• Shiny
• ETL