The automatic creation of OLAP cube using an MDA approach

Abstract

Summary The Model‐Driven Architecture (MDA) is an approach that aligns modeling and automation for software development. By applying such an approach to data warehouse (DW) projects, we can minimize a great deal of time and cost. Furthermore, most of OnLine Analytical Processing (OLAP) platforms seem to be like black boxes that provide wizards only to business intelligence developers to create and manipulate OLAP objects without allowing their sustainability and migration from a platform to another. That is why many works in the literature have proposed using the MDA approach in DW projects. However, most of them have mainly focused on the generation of the DW relational model from the conceptual one, and they overlooked the OLAP model and the cube implementation. To deal with this problem, we propose in this paper an MDA solution to automate the process of getting OLAP cube and its implementation through a set of metamodels and automatic transformations among them. In fact, the proposal generates the OLAP and DW relational models (PSMs) from the conceptual one, using also a PDM model that describes the target business intelligence platform. After that, the source code to create the cube is got from both PSM models. For this aim, we define a set of transformation rules implemented using the Atlas transformation language. Finally, a case study will be provided to validate our approach.

Modeling and automatic generation of data warehouse using model-driven transformation in business intelligence process

“…Last but not least [6], [7] suggested an MDA approach to obtaining an OLAP cube and its implementation by automating the transformations process from metamodels. Compared to the mentioned cited works, this paper aims to rethink and to complete the work presented in [6], [7], by applying the standard QVT and Acceleo to develop the transformation rules aiming at automatically generating the SQL code of data warehouse relational model and XML file of OLAP cube. It is the only work for reaching this goal.…”

“…The advantage of these standards is the bidirectional execution of transformation rules. In this respect, the purpose of this research is to rethink the work [6], [7] by using MDA concepts to develop the transformation rules aimed at generating OLAP cubes and data warehouse relational implementation, and then any user can create a data warehouse without the need for detailed knowledge on BI tools. This paper is organized as follows: related works are presented in the section 2, the section 3 explains our proposed method.…”

Designing business intelligence (BI) for production, distribution and customer services: a case study of a UAE-based organization

“…In most business applications, a reporting component is vital, either to summarize the data by generating a large number of personalized documents or simply to facilitate printing in various information formats (Letrache et al , 2017). This task within a customer database is essential, and JPivot was also used to do it.…”

A Data Cube Metamodel for Geographic Analysis Involving Heterogeneous Dimensions

“…Other studies propose metamodels to help developers for data cubes design [51] or to include OLAP in more general big data architectures [40]. Eventually, more recent studies use metamodels for the automatic implementation of data cubes based on conceptual models [52] (model-driven architecture) and for the automatic instantiation of data cubes based on external data sources [39]. Like CWM, most of these UML metamodels allow data cubes to share dimensions but do not consider constellation navigation in greater depth.…”