Sam Suber writes: “Ever wonder how Netflix seems to recommend shows you end up loving even if you have barely rated anything? Behind the scenes, systems like Netflix rely on a process called data imputation. Data imputation works by filling in the missing values so predictions can still be made. Libraries face similar challenges. There could be gaps in circulation logs, survey responses, or even vendor usage reports. Working with imperfect data is part of the job. But don’t worry—incomplete data does not mean useless data, and it does not require coding knowledge to fix.”