During the data collection process, no one really knows when or how many times the data will be imperfect. Consider what happens when a book is published - e.g., in broad terms, a printer takes the manuscript, reproduces the book many times over, and puts a cover on the copies. The printing machines are specifically set up for the printing of that book. Yet during the printing process, some books will be defective. When they are defective, they are set aside.
Raw data behaves very much in the same manner.
This data must be set aside from the rest of the raw data set, even when at first glance they might appear to be within reasonable limits. A researcher must understand and apply the concepts of accuracy, precision and reliability. Accuracy, precision and reliability describe key data attributes which affect the level of quality and the applicability of the collected raw data. A good way to understand these terms is to envision yourself at a target range. The target is in front of you.