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Data Science project
in IT4BI Master Program
Universite Francois Rabelais Tours
(Blois campus)
Master Program: Universite Francois Rabelais Tours
The University of Tours (French: Université de Tours), formerly François Rabelais University of Tours (French: Université François Rabelais), is a public university in Tours, France.
Full scholarship from the European Commission, 100% covering tuition, living costs and medical insurance
Only 1% of the students that applied received the scholarship
Finished top 3 in the Master Class of 20 students
Data warehousing:
Analysing Labor Data
Business Problem
The primary aim of the project was to construct a data warehouse for Analysing Labor data.
During the life cycle of the project, try and work with different tools and more specifically to handle challenges that come up during the design and construction of the data warehouse.
Role & Responsibility
Identification of data sources, build the conceptual model and corresponding logical schemas.
Data Quality using Excel and Data Cleaner.
ETL using SQL Server Integration Services (SSIS) from Microsoft.
OLAP analysis over data warehouse and optimized performance.
Exploratory data analysis of different usecases.
PowerBI visualization of the final reports.
Objective
The objective of this project is to design and implement a data warehouse for the analysis of labor data.
The data warehouse detailed below is designed to include historical data such as: income, working hours, personal demographics, household information, education, industry and occupation.
Considering the expected analysis, the sources were identified and chosen based on their:
● Granularity we have chosen datasets with high granularity to insure we have a considerable amount of data. Unlike most of the data sources available online which are already aggregated, we have identified microdata sources. This will allow us to perform more interesting aggregations and analysis.
● Organisation the datasets chosen are given well known formats as CSV and STATA.
● Data quality the sources found have been used in previous research, which ensures us that the datasets have reasonable quality.
● Authenticity all the datasets chosen come from renowned organisations such as the US Census Bureau and reported by the Bureau of Labor Statistic.
Report on the results
FinalReport_ADW - Google Docs.pdf
Presentation of the project & results
Google Sites
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