Non-Ferrous Metals Plant Enhancement via Big Data Accumulation, Processing and Analytic

Given the rapid growth of structured and unstructured data and the evolution of customer/consumer analytical needs, client needs a methodical approach to assessing and prioritizing opportunities in order to drive profitable sales growth through Big Data and Analytics. The main aim of this master thesis is to investigate how to enhance the model of non-ferrous metal plant using modern information processing and analysis systems, and management tools. Main research method for data gathering is deductive trend search using literature review for theoretical reasoning and analysing the phased-designed model of Enterprise transformation. The literature review and document analysis show different frameworks (such as TOGAF), trends, methods and benefits of using new technologies (such as SAP S/4 HANA). The applied model of organizational transformation identifies the company readiness for changes and how the organization can continue to grow their analytical maturity. This research solution shows the various advantages of implementing SAP S/4 HANA and using different Big Data analysis methods, and how it can help to increase the business transparency.