Edgar Jullien, Antoine Settelen, Simon Weiss
~4 days development
Story link : https://13w13.github.io/U5-Advanced-Data-Visualization-Tableau/
You are data scientist for the Immo-Inv (a real estate agency) who wants to understand very well the real estate french market, that can ultimately help them build robust models to predict future prices fluctuations or to estimate the price value of a property. In this project, your goal is to perform a data exploration to have a good understanding of available variables and the market with a real world 5-years historical sales transactions for the top 9 french cities (Paris, Marseille, Lyon, Toulouse, Lille, Bordeaux, Nice, Montpellier, Nantes).
The raw datasets contain for each year (from 2015 to 2019) each sale transaction detail :
- sale date
- sale type
- Price
- Postal code
- Address
- Commune
- City
- Number of lots (total number of lots for an apartment or house located in a condominium)
- Local Type
- Living Area (in square meter)
- Land Area (in square meter)
- Number of rooms
- Organize yourself within groups of 3 students (2 students exceptionally).
- Send your tableau prep workflow file (.tfl) and your tableau workbook (.twb file) that contain your data story with your best findings
- Also Send a PDF document, where you explain all your most important design choices, for
example:
o The main choices you made when preparing your data
o How does your visualizations leverage at least one “pop-out effect” or “pre-attentive attribute?” Which one(s) was (were) chosen and why?
o How does your design reflect an understanding of cognitive load and clutter?
o Which metric(s) you have used? and why?
o What is (are) the most important(s) dashboard design principle(s) you have used?
o What is (are) the most important(s) data stories design principle(s) you have used?
o Why do you think your data story meets the audience’s needs? - Your data story should contain at least two dashboards and at least one map chart
- Your data story should contain at least 8 story points