Development of a data mart to support decisions in fashion retail store localization

The evolution of business intelligence began decades ago with the first report mainframe, called the system output. They were mainly printed on paper, to then be distributed periodically to the manager. The first queries have sped up the process and made it possible for managers with technical expertise to create customized ad hoc reports, but few managers had the time and the skills to do so. The emergence of the data warehouse has given a great impetus to the BI aggregating all the data in one place, where he could be interrogated interactively without impacting applications with online queries and reports with increasingly easy graphical interfaces use. The advent of the data warehouse, the data marts and analytic analysis tools have made BI accessible to more operators and allowed managers to obtain information and critical responses efficiently and quickly. The proposed project will be dedicated to the detailed description of the creation of a data mart dedicated to the sales of the fashion company through an optimal solution of best practices of an ETL process resulting in the Snowflake schema and the Star schema, perfect for the data visualization. In addition, using the classification process including both corporate open data, I had the possibility of locating the most effective area to open a new store and to offer an explanation as to why some shops were closed in the recent past. In conclusions, which will be displayed in Power BI, Microsoft software for data visualization.