How Clean is Your Data?


Did you know that (similar to laundry, dancing, and martinis) data can be dirty? Manual input processes, employee turnover, and a lack of time are all contributors to  poor data hygiene. Which hinders your ability to make sound, data-driven decisions. The start and end of academic years are a great opportunity to check-in with your data structures. Taking the time to ensure data cleanliness can seem like a tedious task, but some clear guidelines and regular maintenance can go a long way. Here are some prime areas to inspect:


Naming Formats: Dashes, abbreviations, and spaces can cause confusion when ingesting data. Consider using a standard naming convention to provide a guideline for how data should be entered.


File Structures: Inconsistent organization and unnecessary duplications can add noise to the data.


Permissions and Accounts: While The Great Resignation vexes us all, the effect of turnover on the retention of institutional knowledge is an evergreen problem. Checking permissions in data sources, particularly those containing FERPA-protected data, can help to reduce risk.  


ExamSoft Categories: Old versions of categories that aren’t cleaned out of systems can potentially add confusion when faculty are tagging items. Archive or disable old categories when they are no longer needed. 


ExamSoft Reused Courses: One of the most common data issues we encounter is an ExamSoft environment set up to reuse course shells, removing important information that differentiates courses from each other. It’s never too late to clean this environment up. 


Any and all of these data cleanliness concerns can be overcome with some light, but regular, cleaning. Your Customer Success Team is here to help! 

Meagan Mielczarek, Ph.D.
Head of Education and Assessment at Enflux