Fuzzy Data Matching

Data matching, also know as record linkage, is a fundamental process for many business applications, including duplicates detection, single view of customer, reporting, master data management, fraud detection, terrorism watch lists, along with many others.  Data matching involves linking data records from multiple source systems that do not have a unique key to tie them together. A number of attributes or columns are used in the match process and in general these are text columns.  This requires a comprehensive match solution with the following capabilities:

  • Match data accurately with flexible business rules
  • Scalability with increasing data volumes
  • Flexible match options to support real time and batch mode match options
Factors which are critical for an accurate match process:
  • Ability to handle the variations and other noise in the data records using a variety of fuzzy matching algorithms
  • Data standardization, such as address, name, and other descriptive fields
  • External data enhancement of data to fill in missing or changed values
Performance and scalability issues with increasing data volumes:
  • Match performance on a Multi CPU/Multi Core system falls off exponentially with increasing data volumes
  • Increasing data volumes lead to increases in hardware and license cost
  • Longer time for the match process to complete as the data volumes increase
OpenDQ with its ZERO license cost offers one of the most comprehensive and cost effective data matching solutions. OpenDQ is an integrated solution that supports real time matching and massively scalable matching.

Call us today at 1-877-576-1971 ext 203 or email us at This e-mail address is being protected from spambots. You need JavaScript enabled to view it