Data quality is an area to which everyone pays lip service, but in which few want to invest time or resources. This chapter discusses when and why data validation is useful, and what the consequences of failing to check input and output data are likely to be. The widely used phrase “garbage in, garbage out” is discussed, and the case is made for data professionals to take a kind of “Hippocratic Oath”—in fact, the start of the Hippocratic Oath. Attention then turns to some of the ways in which data can be valid or invalid, and to some common objections to performing data validation. The chapter closes with a discussion of different kinds of null values, introducing a distinction between what will be called x -nulls and μ-nulls.