Course satisfaction surveys play a relevant role in Higher Education, aiding in the quality assessment of courses and informing academic promotions. Nonetheless, understanding potential biases and influential factors within these surveys is crucial to their equitable utilization within universities. This study delves into a deconstruction of satisfaction ratings considering three learning design factors (content, methodology, and workload) and their interplay with student grades. Especially emphasizing the need for institutional analytics to engage in Generative Uncertainty, aiding productive inquiries using data. Institutional analytics of the 2021-2022 and 2022-2023 survey results from a Spanish university revealed that learning design aspects strongly correlate with students' holistic perception of a course. The correlation between student grades and student satisfaction related to learning design is either weak or moderate. These analytical findings imply that there may be bias in students' responses to course satisfaction surveys (e.g., lower grades leading to lower satisfaction). However, this bias doesn't consistently manifest.