A Multi-layer Modeling for the Generation of New Architectures for Big Data Warehousing

Abstract

With the explosion of new data processing and storage technologies nowadays, businesses are looking to harness the hidden value of data, each in their own way. Many contributions were proposed defining pipelines dedicated to Big Data processing and storage, but they target usually particular types of data and specific technologies to meet precise needs without considering the evolution of requirements or the data characteristics’ change. Thus, no approach has defined a generic architecture for Big Data warehousing process. In this paper, we propose a multi-layer model that integrates all the necessary elements and concepts in the different phases of a data warehousing process. It also contributes to generate an architecture that considers the specificity of data and applications and the suitable technologies. To illustrate our contribution, we have implemented the proposed model through a Business model and a Big Data architecture for the analysis of multi-source and social networks data.