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Good quality data is essential to a successful business intelligence application. Most of them are probably aware that Microsoft SQL Server includes some useful data quality tools such as Fuzzy Grouping or Fuzzy Lookup. However, there is one tool people may have overlooked - SQL Server Data Mining. When used operationally, SQL Server Data Mining is extremely useful for finding data that lies outside the boundaries of known good data, and it finds these outliers inductively rather than relying on exhaustively hard-coded rules. This webcast introduces this new, adaptive approach to data quality and shows how adaptive quality can be applied at many phases of the business intelligence project - whether data entry, during warehouse loading, or during analysis.
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