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The quality of software, in particular developed rapidly, is quite a challenge for businesses and IT-dependent societies. Therefore, the H2020 Q-Rapids project consortium develops processes and tools to meet this challenge and improve the quality of the software to meet end-users requirements and needs. In this paper, we focus on data analytics that helps software development companies evaluate the quality of the software. In fact, most software development teams use tools such as GitLab, SonarQube or JIRA (among others) to assess the basic characteristics and metrics of the developed software. In this paper, we propose the framework that gathers basic data from the mentioned tools, and processes the data further (e.g. using Apache Kafka, Kibana and Spark) to calculate more advanced metrics, product factors, indicators, and to find correlations between them. In this paper, we present the concept, the technical details, and the initial results of the advanced data analysis methodology. Furthermore, we provide discussion on how to use the system and show the future development directions. We have already implemented the system at software development SME and managed to find interesting characteristics and correlations about the software quality. The results, based on the real data, were interesting to the company product owners and team leaders, and more importantly helped them improve the software quality development process.

Q-Rapids framework for advanced data analysis to improve rapid software development