EMIGRAID: Design and Implementation of a Decision Support System to Assist People Thinking of Emigration

Kenny, Aideen (2014) EMIGRAID: Design and Implementation of a Decision Support System to Assist People Thinking of Emigration. Diploma thesis, Dublin, National College of Ireland.

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The main objective of this body of work is to build a data warehouse from publicly available data. Integrate this data warehouse with a simple decision support system and visualise the results produced. The subject matter of the database is Emigration and the system is called EMIGRAID. The purpose of EMIGRAID is to help potential emigrants make a decision about where they should move to. The data is gathered from many online sources and contains worldwide emigration movement for the past 50 years, economic indicators, quality of life indicators, temperature and visa information.

The concepts of Data Warehouse(DW), Online Analytic Processing(OLAP), Online Analytic Mining Decision Support Systems(DSS) and Data Visualisation are used. The methods used are to creating a Data Warehouse using SQL, cleanse the data using various data cleansing methods, Extract, Transform and Load into the database, use an SQL and VBA interface to extract information and cut the decision space down, mining the reduced dataset using the kMeans clustering and the kNN classification algorithms. Deal with the problems of classification where no training set exists. This was handled by creating an artificial training set created from the data warehouse itself.

The paper then deals with the benefits of visualisation techniques to enhance the user experience and make the data being presented easier to understand.

The last part of the paper outlines prospects of how EMIGRAID could be further improved.

Item Type: Thesis (Diploma)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Divisions: School of Computing > Higher Diploma in Science in Data Analytics
Date Deposited: 12 Dec 2014 15:03
Last Modified: 12 Dec 2014 15:05

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