Data deduplication is necessary to maintain an accurate master data record. The enterprise needs a single source of truth to maintain consistency and efficacy.
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In master data management, often the same data is duplicated across several departments, which can harm the business. That’s why data deduplication is necessary to maintain an accurate master data record. It includes the removal of duplicate data from the business database. Moreover, master data needs to be a single source of truth for the whole enterprise to maintain its consistency and efficacy.
Data deduplication has many advantages, such as improved cost savings. It helps improve analytics performance by providing the team with the most reliable data. It also helps the company provide a better customer experience.
Some conventional data deduplication strategies include data standardization based on external IDs, fuzzy matching with rules, persistent IDs, enrichment data, and machine learning.
Match merge is a process that can help identify duplicate data in master data. It takes data from different systems and looks for duplicates or exact matches (and merges them if necessary) to make a “golden copy” of the record. The match-merge process can be done in two ways: in real-time or in a batch approved by another method to verify the golden record.
