Meta-Modeling of Big Data visualization layer using On-Line Analytical Processing (OLAP)
Allae Erraissi · International Journal of Advanced Trends in Computer Science and Engineering · 2019
Big data is about collecting, storing, managing, processing massive quantities of daa, but it is also about presenting various insights into the collected data through visualization.Visualization layer is located on the top of a layered architecture composed of Data Sources, Ingestion, Storage, Management, Monitoring, and Security layers.While each of these layers has its own challenges, visualization is presenting a particular challenge because of physical limitations of the display area and the chosen mode of data presentation.Along with the visualization modes, OLAP is a powerful technology for data discovery, including capabilities for limitless report viewing, complex analytical calculations, predictive scenario planning, and visualization.Based on our previous comparative studies in which we identified key concepts of visualization layer of major Big Data distributions, we propose in this paper to map this layer to OLAP visualization technology.To achieve this goal, we apply techniques related to Model Driven Engineering "MDE" to propose a universal meta-model for visualization layer in a Big Data systems, in which we integrated a meta-model of OLAP for data presentation.