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Data Cleaning: Problems and Current Approaches

Data Cleaning: Problems and Current ApproachesErhard Rahm Hong Hai DoUniversity of Leipzig, classify data quality Problems that are addressed by data cleaning and provide an overview of the mainsolution Approaches . Data cleaning is especially required when integrating heterogeneous data sources andshould be addressed together with schema-related data transformations. In data warehouses, data cleaning isa major part of the so-called ETL process. We also discuss Current tool support for data IntroductionData cleaning, also called data cleansing or scrubbing, deals with detecting and removing errors andinconsistencies from data in order to improve the quality of data.

- Referential integrity - Misspellings - Redundancy/duplicates - Contradictory values … Figure 2. Classification of data quality problems in data sources 2.1 Single-source problems The data quality of a source largely depends on the degree to which it is governed by schema and integrity constraints controlling permissable data values.

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