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Data intensive applications that leverage Big Data technologies are rapidly gaining market trend. However, their design and quality assurance are far from satisfying software engineers needs. In fact, a CapGemini research shows that only 13% of organizations have achieved full-scale production for their Big Data implementations.
We aim at addressing an early design and a quality evaluation of data intensive applications, being our goal to help software engineers on assessing quality metrics, such as the response time of the application. We address this goal by means of a quality analysis tool-chain. At the core of the tool, we develop a Profile that converts the Unified Modeling Language into a domain specific modeling language for quality evaluation of data intensive applications. The DICE Profile repository gathers all the profiles of the DICE project.