THE EVOLUTION OF BIG DATA AND DATA SCIENCE, WITH SPECIFIC FOCUS ON THE FASHION INDUSTRY AND TREND PREDICTION
CARDIFF METROPOLITAN UNIVERSITY
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With the “Big Data” era in rapid motion, the number of businesses and organisations from a diverse range of industries adopting data-driven approaches and methodology, to advance business prospects has proliferated continuously. The great potentials in efficiently utilising big data and the birth of the data scientist and analyst have soared and are now considered to be highly valued assets to any company. The following thesis will delve into the importance of big data in the modern era and its subsequent effects on different industries, with specific focus on the fashion industry; an area which data and technology has caused a seismic revolutionary change in the management and operational methods. Adopting a series of different data-driven and analytical techniques, to form a case study surrounded by a chosen fashion retail company to test real data and the strategies currently operated; through the use of an interview to determine and further understand the position of the company. In addition to data exploration, cleaning and visualisation to assess the approach to trend prediction, along with hypothesis testing to enable accuracy in building and testing a prediction model. The concluding results of the explicitly detailed methodology and revised literature identified the requirement of the company, to re-evaluate the data-driven methodology and trend prediction strategies currently implemented, in order to eliminate the fluctuations within the outcomes. Furthermore, the results continue in emphasising the importance of companies from all industries to incorporate and execute forms of data-driven methodology and predictive analysis adroitly in this modern age of technology.
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