In the information age, the policy-making process struggles to effectively integrate findings from data science. Despite the abundance of data, the complexity of concepts and the difficulty in translating complex analyses into concrete policies hinder the full utilization of data. This issue is compounded by the misalignment between short-term political priorities and evidence supported by the data. Furthermore, additional data is often needed to comprehensively frame the problems at hand. Given these obstacles, a key research question is how to effectively communicate findings from data science in policy-making and ensure decisions are relevant and based on solid evidence.