Data Quality Tools Wizards

• To configure data monitoring routines: You should be able to set-up business rules in terms of:

• The target data to be monitored
• Monitoring flow (which monitoring to be done first and which to be done later)
• Exception definition- Setting different levels of exceptions
• The actions to be taken in case of exceptions etc...

• To configure data cleansing routines: The configuration capabilities should include:

• Data Standardization rules
• Data Quality Exceptions
• De-dup rules
• Other Data Correction Rules

• To be able to identify and repair data quality issues: A wizard should allow you to interactively fix these issue or/and take decisions around them. For example, if there are customer records, which have grabled data around the age of the customers, you may decide to apply the extrapolation method, or place a default value or place a median value etc...

• To configure rules for data searching and matching: Typically for customer data, many of the searching and matching rules come pre-defined. Apart from that, one should be able to set-up:

• The extent of match, before the records can be stated as matching
• Number of N-grams which should match, before one can say that records are matching
• Defining patterns for matching etc...