The food industry is facing the dual challenge of increasing production and reducing its environmental impacts. Climate Smart Agriculture (CSA) seeks to establish both technological enablers and farming practices to meet the requirements concerning improved productivity and lower environmental impacts. The digital transition plays a key role in CSA, since digital technologies and data are necessary enablers of measuring, monitoring, and verifying production and the climate impacts of agriculture. Therefore, data-driven approaches based on IoT, AI, remote sensing, robotics, and smart sensors, for example, can be used to develop farm management and decision-support systems for various purposes in CSA. Digital technologies generate farm-level data that farmers are expected to share with their stakeholders (industry, government, technology businesses, and research institutions). This has resulted in an urgent need to develop user-centric solutions to support decision-making on the farm level. In this paper, we study how agricultural data can be used to assist informed decision-making in CSA by means of a qualitative, interview-based study. The results reveal that the data collected from farming activities, the environment and other sources has the potential to be used as a basis for rationally oriented and systematic planning, decision-making and prediction that could gradually replace the traditional sense-making-based planning.