Verinin bilgiye dönüşümünde büyük-veri sistemlerinin fayda ve maliyetleri

This thesis explains problems of and solutions for storing and processing big volumes and streaming types of data in a cost-e ective way for enterprise companies. There are several problems like operational, infrastructural and usability problems about these new concepts of Big Data. The basic data processing concepts are not new, but the data generation volumes and velocities are pushing the limits of centralized architectures. Distributed systems using distributed programming models such as the Hadoop framework are used today to handle big data problems. This thesis will try to combine the structural, architectural and nancial issues to address big data storage and processing problems and will give practical examples based on real-life experiences from several big data applications in di erent sectors including mobile telecommunications, nance and oil-gas elds.