MDA Transformation Process of A PIM Logical Decision-Making from NoSQL Database to Big Data NoSQL PSM
Fatima Kalna1, Abdessamad Belangour2, Mouad Banane3, Allae Erraissi4

1Fatima Kalna, Laboratory of Information Technology and Modeling, Hassan II University, Faculty of sciences Ben M’Sik. Casablanca, Morocco.
2Abdessamad Belangour, LTIM, Hassan II University. FSBM. Faculty of sciences Ben M’Sik. Casablanca, Morocco.
3Mouad Banane, Laboratory of Information Technology and Modeling, Hassan II University, Faculty of sciences Ben M’Sik. Casablanca, Morocco.
4Allae Erraissi*, Laboratory of Information Technology and Modeling, Hassan II University, Faculty of sciences Ben M’Sik. Casablanca, Morocco.
Manuscript received on September 22, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 4208-4215 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1619109119/2019©BEIESP | DOI: 10.35940/ijeat.A1619.109119
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Business Intelligence or Decision Support System (DSS) is IT for decision-makers and business leaders. It describes the means, the tools and the methods that make it possible to collect, consolidate, model and restore the data, material or immaterial, of a company to offer a decision aid and to allow a decision-maker to have an overview of the activity being treated. Given the large volume, variety, and data velocity we entered the era of Big Data. And since most of today’s BI tools are designed to handle structured data. In our research project, we aim to consolidate a BI system for Big Data. In continuous efforts, this paper is a progress report of our first contribution that aims to apply the techniques of model engineering to propose a universal approach to deal with Big Data is to help decision-makers make decisions.
Keywords: Model Driven Engineering; meta-model; business Intelligence; Big Data.