The 4 Cs of Data Quality
Nothing quite sums up the importance of data quality like the well-known phrase “garbage in, garbage out.” Without good data, you cannot have good analysis; data quality is required for sound decision-making.
As a guide, it’s crucial to keep in mind the 4 Cs of data quality: the consistency, conformity, completeness and currency of the data. Consistency means ensuring a clear picture of data consistency—meaning, is it statistically valid? Is it internally coherent? Are there extreme values, outliers or anomalies? Conformity refers to acceptable standards and patterns that the data must adhere to or ensuring there are no mismatched values. Completeness indicates that all necessary data has been included and there are no missing values. And finally, currency, or validating that the data is up-to-date and has been refreshed regularly.