Model-Driven Engineering for Data Intensive Applications
Big Data technologies have rapidly achieved widespread adoption for many reasons, e.g., thanks to the versatility with which they foster innovative products by direct analysis of various user contents (e.g., tweets, blogposts, likes, pictures, etc.). However, designing and developing Big Data applications is still a considerable problem since: (a) it involves many side-costs the time spent on learning about and designing with the many big data frameworks; (b) it requires to balance out infrastructural and corporate governance costs with (non-trivial) development and deployment costs; (c) it most likely requires additional costs for the various trial-and-error experiments needed to match desired performance. We argue that a relevant part of said costs can be saved by tackling the design, development and deployment of Data Intensive Applications (DIAs) with Model-Driven Engineering (MDE) framed into a DevOps process. The purpose of this course/presentation is to show how MDE and DevOps have been applied to the design of Data Intensive Applications and to identify new research areas and issues.
Lecture at NEMO2016
Date/Time: Thursday, July 28, 2016 at 11:30