A multi-criteria group decision making method for big data storage selection

Abstract

The terms Data Lake and Data Warehouse are very commonly used to talk about Big Data storage. The two concepts are providing opportunities for businesses to better strengthen data management and achieve competitive advantages. Evaluating and selecting the most suitable approach is however challenging. These two types of data storage are often confused, whereas they have many more differences than similarities. In fact, the only real similarity between them is their ability to store data. To effectively deal with this issue, this paper analyses these emerging Big Data technologies and presents a comparison of the selected data storage concepts. The main aim is then to propose and demonstrate the use of an AHP model for the Big Data storage selection, which may be used by businesses, public sector institutions as well as citizens to solve multiple criteria decision-making problems. This multi-criteria classification approach has been applied to define which of the two models is better suited for data management.