Translational research applies findings from basic science to enhance human health and well-being. In translational research projects, academia and industry work together to improve healthcare, often through public-private partnerships. This “translation” is often not easy, because it means that the so-called “valley of death” will need to be crossed: many interesting findings from fundamental research do not result in new treatments, diagnostics and prevention. To cross the valley of death, fundamental researchers need to collaborate with clinical researchers and with industry so that promising results can be productized. The success of translational research projects often does not only on the fundamental science and the applied science, but also on the informatics needed to connect everything: the translational research informatics. This informatics should enable the researchers to store their ‘big data’ in a meaningful way, to ensure that results can be analyzed correctly and enable application in the clinic. The author has worked on the IT infrastructure for several translational research projects in oncology for the past nine years, and presents his learnings in this paper in the form of ten commandments. These learnings are not only useful for the data managers, but for all involved in a translational research project. Some of the commandments deal with topics that are currently in the spotlight, such as machine readability, the FAIR Guiding Principles and the GDPR regulations, which might mean that they no longer need to be mentioned in an overview like this within a few years. The other commandments might still be noteworthy in many years to come.