| Alison Celigoi, Nicole Gonzalez |
Identifying critical differences is crucial for maintaining data continuity and data integrity, whether in comparing longitudinal datasets over years or comparing datasets for changes or other updates. Data managers and SAS programmers often need to meticulously compare datasets to identify structural changes such as variable names and attributes. To address these needs, ICF has developed a sophisticated SAS program designed to compare dataset structures seamlessly and efficiently. The program thoroughly evaluates the datasets being compared, examining attributes such as labels, formats, variable types, lengths, and dataset order, and presents any disparities in a user-friendly Excel spreadsheet. Automating this process saves time and minimizes the risk of human error. Armed with this information, programmers can manipulate dataset shells to achieve desired outcomes and harmonize datasets. In this presentation, we will provide a step-by-step walkthrough of the SAS code and apply it to a dataset from the SASHelp library and a slightly altered dataset that we will create for comparison. Finally, we will review and discuss the output produced, and how it applies to final data resolution. |