HomePoint is a project aimed to rank countries performance based on several different criteria for example, life expectancy, happiness, wages, cost of living, safety/crime rates and more. This project aims to dive deep into what exactly it is that makes a country great to live in and what factors people really value the most. Using this project, a user should be able to find their perfect place to live and potentially even point them to their next home. Using Tableau, HomePoint is used as a tool to find several different interesting patterns which emerge throughout different countries in the world. The user will be able to carry out their own analysis as Tableau can be highly interactive and user friendly. In order to gather the findings and results, various different techniques were be used such as machine learning, clustering and other techniques. In order to merge various data sets together, code in R studio is used to ensure all relevant information is correctly organised and ready for use in different types of visualisations. HomePoint has the capability to show the weak aspects of countries allowing the user to compare different countries. Governments could use this information to understand what people value and what improvements they can make to their country under the different categories.
R, Tableau, Excel, Python
Final year computing student specialising in Data Analytics. 8 months experience working at ESB as an IT intern running queries on ESB's Oracle and SAP databases, developed a Sharepoint platform including requirements gathering and all necessary documentation. Also greatly developed teamwork skills and organisational skills. Highly computer literate with a huge passion for technology, with knowledge in Java (including AI), R, C#, HTML5, CSS, SQL, XML, operating systems, MySQL, JSON etc. Keen interest in data analytics as well as its real life implications and uses. Experience working as a translator and customer services representative in the family business. Fluent in English and Polish.