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7. Organizing Data > Clean Inconsistent Records

Clean Inconsistent Records

Sometimes you have to import tables with redundant data that is “nearly” right. There are some tricks you can use to make the process easier.

You may come across a system where a one-to-many relationship has been implemented incorrectly. There is no easy way to recover from this. Someone is going to have to sift through the data by hand to fix any anomalies.

Look at the table of library books shown in Table 7-12.

Table 7-12. book, a poorly normalized table with inconsistent data
barCodeisbntitleauthor
BC0010140430423Hard TimesCharles Dickens
BC0020586089195BluebeardTurk Vonnegut
BC0030586089195BluebeardKurt Vonnegut
BC0040586089195BluebeardKurt Vonnegut

The library has three copies of Bluebeard and the book title and author have been typed in three times. This has led to a problem because the author’s name, Kurt, has been misspelled as “Turk” for BC002. Once you have the data properly normalized that sort of inconsistency will be impossible to create.


  

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