Customer Duplicate Resolution

Pretectum’s CMDM deduplication is to identify and eliminate duplicate records within the customer data stored in the Pretectum CMDM.

Duplicate records can occur for various reasons, such as data entry errors, system migrations, or lack of data governance.

Duplicate customer records can lead to inefficiencies, inaccuracies, and inconsistencies in business operations, customer service, and reporting.

Deduplication aims to address these issues and achieve several important goals among them record matching is driven by the data tagging and classification process. This is done to ensure that you are able to use the most effective means of duplicate record identification.

Two types of duplicate record matching are available: exact matching that is based on one or more data classifiers and fuzzy matching that is based on the relative closeness of text strings and values.

For many cases, exact duplicate matching on one or more criteria often resolves many cases but the suitability of exact matching really hinges on what you determine to be the most critical data elements in your customer master.

Contact identifiers are often the most consistent and most popular. Ensuring that your data quality is optimized up-front improves the duplicate matching process also. 

Duplicate matching is undertaken as a batch process that can be executed across schemas and across datasets.