This workshop introduces a practical approach to data validation with pointblank in R. Participants begin by inspecting datasets and identifying which characteristics need explicit checks. The session then explores how to express useful validation rules that reveal current problems and help detect issues in future data updates. Reporting is a central part of the workflow, with attention to communicating findings and adapting the available reports. Additional topics include filtering records according to data quality and investigating the causes of failed checks. The workshop connects initial data inspection, validation design, and clear reporting into a repeatable approach to data quality assessment.