Rapport Business intelligence

 2015-2016

Housing in Tunisia

in cooperation with CNS

Plan

Plan .......................................................................................................................................................... 2

Introduction ............................................................................................................................................. 3

Project context ........................................................................................................................................ 4

Modeling ................................................................................................................................................. 5

Data Integration ...................................................................................................................................... 7

Analysis and reporting ............................................................................................................................. 8

Big Data ................................................................................................................................................. 12

Data mining ........................................................................................................................................... 16

Figure 1 Data warehouse model 6

Figure 2 Extract Transform Load (ETL) 7

Figure 3 Number of sales per year 8

Figure 4 Cities classification per number of sales 8

Figure 5 Cities classification per square meter price 9

Figure 6 Regions classification per number of sales 9

Figure 7 Sales global Dashboard 10

Figure 8 global Dashboard 10

Figure 9 Dynamic map of sales information 11

Figure 10 Big Data: Facebook 13

Figure 11 Big Data: Twitter 14

Figure 12 Correlation between variables 16

Figure 13 m² price evolution 18

Figure 14 Correlation between sales and m² price 18

Figure 15 Sales number in function of time 19

Figure 16 m² price in function of time 20

Figure 17 Essour activities distribution 20

Figure 18Essour word cloud 21 3

Introduction

Nowadays, data is important to make decisions, but we have a huge amount of raw data that could alter the visibility in order to reach our goals, and take the proper decisions.

Data are now woven into every sector and function in the global economy, and, like other essential factors of production such as hard assets and human capital, much of modern economic activity simply could not take place without them.

Business Intelligence could be the alternative to give sense to a big quantity of raw plain data to make meaningful and useful information.

For example, it could be a solution to have an idea about the evolution of housing in Tunisia which faces today a lot of challenges. 4

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