Mixed Source Data Engineering & Analytics: a best of both worlds approach [Dutch spoken]

Erasmus University Rotterdam (EUR) is one of the largest academic institutions of the country whose mission is ‘creating a positive societal impact’, and where the United Nations Sustainable Development Goals serve as a compass for research and education alike. With the variety and diversity of topics within EUR, an open, flexible, affordable, and easy to use data & analytics solution is key to support data & AI projects. At the same time there are many internal and external factors that need to be considered: the adoption of and migration to cloud solutions, the push for open science and open source, an ever faster changing technology landscape, and finally the breathtaking speed with which AI solutions are coming to market. Making future proof choices in this environment is a daunting task as one could imagine. Nevertheless, choices have been made and consist of a mix of open source and proprietary solutions, both on-premise and in the cloud, and guided by modern software engineering principles. This session will highlight the following:

• The influence of modern software engineering principles like CI/CD on data engineering, data management, and analytics
• How to remain independent and prevent lock in from any vendor or cloud provider
• The tradeoff between building, buying, and renting hard and software
• How to standardize on tools and technology and remain flexible at the same time.