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This dissertation was written as a part of the MSc in Data Science at the International Hellenic University. The main purpose is the presentation of the Business Intelligence and Data Warehouse concepts in a theoretical way firstly so as to reflect the important and necessary concepts regarding business intelligence requirements and simultaneously how businesses can respond to the exponentiality of technological changes. Since a Data Warehouse is of vital interest, thorough the core of this Thesis are explained the main definitions, concepts, technical architectures and structured models of Data properties and Data Warehouse in general. It is aimed to offer a comprehensive understanding of the role of data warehousing in business intelligence. Extract, transform, and load (ETL) processes constitute an integral part of Data Warehousing, owing to allowing data to be extracted from a variety of sources, transformed into a standardized format, and loaded into a central repository for analysis. These concepts and knowledge are utilized at the last part of this dissertation by examining a real Dataset from a well-known Czech Republic’s bank by employing real world techniques, leading in real world scenarios that constitute useful results that ameliorate business processes and needs.