This presentation is part of the KODAQS Data Quality Academy materials of the Competence Center for Data Quality in the Social Sciences (KODAQS). KODAQS is a joint initiative of GESIS – Leibniz Institute for the Social Sciences, the University of Mannheim, and the Ludwig Maximilian University of Munich (LMU) and is funded by the BMFTR and the EU NextGen Horizon Fund. The KODAQS Data Quality Academy program is designed to build practical and conceptual skills for assessing, documenting, and improving data quality across the entire lifecycle of quantitative research in the social sciences. The program combines core theoretical foundations with applied tools and domain-specific techniques. This presentation covers a missing case study - step by step, how to decide between MI or FIML, and how to detect, handle, and report missing cases. This presentation is the seventh part of a set of presentations on the topic of "Tools and Workflows (Survey Data)".