I define data preparation as making data one currently possesses ready for appropriate statistical modeling conducted in quantitative research. Its importance to proper statistical modeling cannot be understated. While running suitable final models comes down primarily to understanding what models are needed to be run; effective data preparation demands meticulous attention to detail across various tasks. These tasks include, but are not limited to, data restructuring, handling missing data, identifying and potentially removing outliers, transforming variables, and conducting preliminary analyses.
Any inadequacy in performing the aforementioned tasks results in final models that cannot be relied upon, consequently undermining the trustworthiness of key recommendations derived from them. As a result, I dedicate a significant portion of my time directly engaging with data during the data preparation stage.