Every set of data contains some errors. Detecting and removing these oversights, known as data cleansing, can often be a lengthy process. However, efficient data cleansing is essential in order to be able to come to accurate conclusions from data analysis. In addition, one of the principles of the Data Protection Act (described in  Chapter 8) is to ensure that your data is accurate and, when necessary, is up to date.


Frequency Distribution Data Item Typing Error Truncation Error Database Table 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Anna Manning 2015

Authors and Affiliations

  • Anna Manning
    • 1
  1. 1.ChesterUK

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