Companies require data that is both correct and comprehensive. But what parameters should data fall into to qualify as quality data? Quality data should be valid. It should conform to real-world specifications, agreeing with what it’s meant to represent. It should be inclusive, showing, for example, all the demographic information needed. Data needn’t be perfect. However, errors should fall within an anticipated, acceptable range. Data should be integrated, with specific details logged only once. And it should be consistent, so that items like numbers and dates appear across the board, in a uniform way.
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