Chapter 17 - Data Quality

Abstract

Data quality ensures the accuracy and timeliness of data and it is much easier to ensure data quality before data get into a database than after they are stored. To be useful, the data in a database must be accurate, timely, and available when needed. Data quality problems arise from a wide range of sources and have many remedies. One source of data quality problems is missing data. There are two general sources—data that are never entered into the database and data that are entered but deleted when they shouldn't be. Another quality problem is that of incorrect data. Incorrect data is probably the worst type of problem to detect and prevent. Often the incorrect data aren't detected until someone external to an organization makes a complaint. Determining how the error occurred is equally difficult because sometimes the problems are one of a kind. Data can sometimes also be incomprehensible. Unlike incorrect data, it is relatively easy to spot incomprehensible data, although finding the source of the problem may be as difficult as it is with incorrect data. The last problem with data is inconsistency of data. If the data are to be consistent, then the name and address of a customer must be stored in exactly the same way in both databases.