Big Data has been described as a four-dimensional model with Volume, Variety, Velocity, and Veracity. In this paper we discuss the potential of a model-driven approach (MDA) to tackle design issues of Big Data taking into account the effect of the four dimensions. Our approach considers NoSQL graph databases. The approach is applied to the case of Neo4j database. Our main contribution is an MDA methodology that enables to tackle the four V's dimensions described above. It consists of two major steps: (i) a forward engineering approach based on MDA as well as a set of transformations rules enabling the development of a conceptual, logical, and physical model for big data encompassing the four V's, (ii) a volume-guided approach supporting the generation of test bases dedicated to performance evaluation. We present an illustrative scenario of our forward engineering approach.