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Data Scrubbing

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  • First Online:
Encyclopedia of Database Systems

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Synonyms

Data cleansing

Definition

Data scrubbing refers to the task of first identifying data that are corrupted, incomplete, invalid, missing, inconsistent, outdated, duplicated, or irrelevant and then either correcting or removing such “dirty” data. The aim of data scrubbing is to make data more accurate, more complete, and consistent both within and across different tables in a database or data warehouse.

An important challenge of data scrubbing is that “dirty” values do not necessarily contradict any database requirements, i.e., such values are consistent with the design of a database and its schema. Rather, errors occur at a higher conceptual level. Examples include credit card numbers that follow a correct grouping of four-times-four digits but that are invalid with regard to a check-sum algorithm, or addresses that have a valid zipcode value that is inconsistent with the town and state names in the same record. Such errors can occur because of a lack of checks and validation...

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Recommended Reading

  1. Batini C, Scannapieco M. Data quality: concepts, methodologies and techniques, Data-centric systems and applications. Berlin: Springer; 2006.

    MATH  Google Scholar 

  2. Christen P. Data matching – concepts and techniques for record linkage, entity resolution, and duplicate detection, Data-centric systems and applications. Berlin: Springer; 2012.

    Google Scholar 

  3. Fan W, Geerts F, Jia X, Kementsietsidis A. Conditional functional dependencies for capturing data inconsistencies. ACM Trans Database Syst. 2008;33(2):6.

    Article  Google Scholar 

  4. Lee Y, Pipino L, Funk J, Wang R. Journey to data quality. The MIT Press; Cambridge, Massachusetts, 2009.

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  5. Maletic JI, Marcus A. Data cleansing: a prelude to knowledge discovery. In: Data mining and knowledge discovery handbook. Springer; New York, US, 2010, p. 19–32.

    Google Scholar 

  6. Rahm E, Do HH. Data cleaning: problems and current approaches. IEEE Data Eng Bull. 2000;23(4):3–13.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Research School of Computer Science, The Australian National University, Canberra, 2601, Australia

    Peter Christen

Authors
  1. Peter Christen
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Corresponding author

Correspondence to Peter Christen .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, Georgia, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, Ontario, Canada

    M. Tamer Özsu

Section Editor information

  1. Information Systems, Hasso-Plattner-Institute, Prof.-Dr.-Helmert-Str. 2-3, 14482, Potsdam, Germany

    Felix Naumann

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© 2016 Springer Science+Business Media New York

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Christen, P. (2016). Data Scrubbing. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_80621-1

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  • DOI: https://doi.org/10.1007/978-1-4899-7993-3_80621-1

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  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4899-7993-3

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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