Numerous data quality (DQ) cleansing tools are available to assess and cleanse source data before any ETL process is run for data integrations, data migrations, data warehouse loads, and analytic applications. The objective of this message is to outline the needs for testing data after it has been cleaned to ensure that the expected results were achieved.
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