Data Cleansing

Information is only as good as the source, and having incomplete or inaccurate data can lead to incorrect information. Not only does this not provide the details that are needed, but there might be issues in integrating the data. In the previous chapters we discussed methods to integrate data to make it useful; however, the quality of the data also needs to be considered.

Data quality defines the successfulness of an integration. Being able to provide consistent and complete data that is integrated with other systems for a “big picture” view will show the value of data. The data quality process might already be part of ...

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