This course guides researchers through the entire data lifecycle from initial acquisition to visualisation. Researchers begin by learning robust data cleaning and preparation techniques, such as handling duplicates, splitting cell contents and utilising VLOOKUP, before progressing into advanced exploratory tools like Pivot Tables and Pivot Charts. The course places a strong emphasis on data integrity and plausibility checks to ensure researchers can identify errors in complex datasets, including specialised time series data. By the end of the course, researchers will be equipped to automate workflows using macros, implement data validation and create publication quality charts, such as radar and scatter plots, while also understanding when to transition from spreadsheets to more advanced database systems.