Table of Contents


  1. Introduction
  2. Configuring Hub Console Tools
  3. Building the Data Model
  4. Configuring the Data Flow
  5. Executing Informatica MDM Hub Processes
  6. Configuring Application Access
  7. MDM Hub Properties
  8. Viewing Configuration Details
  9. Search with Solr
  10. Row-level Locking
  11. MDM Hub Logging
  12. Table Partitioning
  13. Collecting MDM Environment Information with the Product Usage Toolkit
  14. Glossary

Search Levels

Search Levels

Used with fuzzy-match base objects only. When you configure a match rule set, you define a
search level
that instructs
Informatica MDM Hub
on how stringently and thoroughly to search for candidate matches.
The goal of the match process is to find the optimal number of matches for your data:
  • not too few (called
    ), which misses relevant matches, or
  • not too many (called
    ), which generates too many matches, including matches that are not relevant
For any name or address in a fuzzy match key,
Informatica MDM Hub
uses the defined search level to generate different key ranges for the purpose of determining which records are possible match candidates—and to which records the match column rules will be applied.
You can choose one of the following search levels:
Search Level
Most stringent level in searching for possible match candidates.This search level is fast, but it can result in fewer matches than other search levels might generate and possibly result in undermatching. Narrow can be appropriate if your data set is relatively correct and complete, or for very large data sets with highly matchy data.
Appropriate for most rule sets.
Generates a larger set of possible match candidates than the Typical level. This can result in more matches than other search levels might generate, possibly result in overmatching, and take more time. This level might be appropriate for smaller data sets that are less complete.
Generates a still larger set of possible match candidates, which can result in overmatching and take more much more time. This level might be appropriate for smaller data sets that are less complete, or to identify the highest possible number of matching records.
The search level you choose should be determined by the size of your data set, your time constraints, and how critical the matches are. Depending on your circumstances and requirements, it is sometimes more appropriate to undermatch, while at other times, it is more appropriate to overmatch. Implementations dealing with relatively reliable and complete data can use the Narrow level, while implementations dealing with less reliable data or with more critical problems should use Exhaustive or Extreme.
The search level might also differ depending on the phase of a project. It might be necessary to have a looser level (exhaustive or extreme) for initial matching, and tighten as the data is deduplicated.


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