Data Matching and Entity Resolution

The Data Matching feature is integral to maintaining the integrity of master data within the DOCK Integration Framework. It is designed to assess and relate incoming records to existing data within the MDM database, ensuring accuracy and consistency across member information.

Functionality:

• Candidate Selection: Identifies potential matches for a member record based on predefined criteria.
• Comparison: Evaluates similarities between potential matches using weighted comparison functions.
• Scoring: Calculates a score to determine the likelihood that records match.
• Linking: Associates matching records or flags them for further review based on score thresholds.

Benefits:

• Provides a systematic approach to identifying and merging matching records, reducing duplication and enhancing data quality.
• Facilitates flexible configuration to handle data matching in real-time or batch processes, accommodating different operational needs.

Purpose:

• To automate the process of recognizing and consolidating member records, while allowing for manual review where necessary.
• To support effective entity management by defining clear rules and thresholds for linking data.

Operation:

• The process commences post-data derivation, utilizing the derived standardized and comparison data for matching.
• An Entity Manager, configured within the operational server, manages the matching workflow, operating in either continuous, synchronous, or asynchronous modes to suit frequent updates or batch processing.
• Depending on system configuration, the MDM server can automatically link records, generate tasks for manual review, or both, using the scores generated during the comparison.

This feature is designed to ensure that the member data within the MDM system is accurately matched and linked, contributing to the reliability of the overall data management process.