BDD-Immo

Data Base for property prices's predictions and recommandation

Laplace Immo is a property agency based in France. They want to improve their offer by proposing a better prices recommandations to their client. In the purpose of this project, as a Data Analyst working for Laplace Immo, I'm in charge of build the new data architecture.

DB first approach

All data we needed to store in a Data Base are as following :

• Property sales in France for half-year period of 2020
• Caracteristics about properties (number of rooms, size, type)
• Street adress of the real property

Using of PostgreSQL as DBMS

We propose to open a PostgreSQL server. Postgre offer us a easy to use admin interface for monitoring and requesting data base. We use table_create written in SQL to build tables and relationnals dependancies

• UML diagram here (open file with draw.io)
• 3NF relational schema here (open file with Power Architect Software or similar)
• Import table from here

DB installation

1. run table_create.sql as a SQL program in a PostegreSQL's shell
2. get cleaning data for feeding the DB here
3. import data in PostegreSQL

Application

Get free to request the DB to understang the french property market and find your real property at right prices.
Examples are provided into Requete_SQL folder. Click here to test requests with your DB
NB : Data used in this project has been published by the french government

Requirements

• PostgreSQL latest version is preferrable (14.1 released in Nov 2021)
• Installation from Linux, MacOS or Windows platforms
• Power Architect can be found here. Be careful to pick the right version according to your operating system