Consider the following guidelines when you configure declarative rules:
•Analyze your data and determine whether you need an automated or a manual merge strategy.
•Before configuring match rules, profile the data properly. Optimal match rules are derived after iterative tests.
•Create simple declarative rules before moving to complex ones. With this approach, you can refine and improve your match strategy based on the results.
•Use multiple declarative rules to cater to different scenarios and levels of accuracy. For example, you can create a rule for exact matches, another for fuzzy matches, and additional rules for specific attributes or patterns. You can combine these rules using logical operators, such as AND and OR to define the overall match strategy.
•Add one or more exact match fields, such as postal codes or phone numbers to act as filters for each rule. Exact match fields can significantly improve performance by reducing the number of fuzzy matches.
•Use the fewest possible number of declarative rules in a match model for optimal match results.