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Titlebook: Data Cleaning; Venkatesh Ganti,Anish Das Sarma Book 2013 Springer Nature Switzerland AG 2013

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https://doi.org/10.1007/978-3-319-97091-2g updated with fresh data subsequently. hese solutions are typically incorporated into an ETL process which is maintained in order to populate and maintain a data warehouse. A data cleaning solution is expected to address to several critical high level tasks. Some of these tasks include ., ., and ..
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Climate Change, Agriculture and Societyper implementing the data cleaning solution. The more flexible approaches often require the developer to implement significant parts of the solution, while the less flexible are often easier to deploy provided they meet the solution’s requirements.
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https://doi.org/10.1007/978-3-319-40590-2ied by a textual similarity function which compares the content of the two records. There are a variety of common similarity functions as discussed in the previous chapter. As in record matching, the deduplication task typically involves many predicates. However, a critical one is often based on textual similarity between records.
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Task: Record Matching,may have to be solved while deduping records (say, customers or products) in a particular relation. While record matching may be formally defined in multiple ways, below we present a commonly used abstraction:
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Introduction,y has become so important on its own that businesses often create consolidated data repositories. These repositories can be observed in several scenarios such as data warehousing for analysis, as well as for supporting sophisticated applications such as comparison shopping.
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Conclusion,g updated with fresh data subsequently. hese solutions are typically incorporated into an ETL process which is maintained in order to populate and maintain a data warehouse. A data cleaning solution is expected to address to several critical high level tasks. Some of these tasks include ., ., and ..
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