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Merge and purge is the process of linking two or more lists or databases at the same time, identifying and/or combining duplicates and removing unwanted records. The objective of the merge/purge practice is to produce a clean set of records, such as unique names and addresses creating a single customer view.  Once you have achieved this you will then cut your costs by mailing only one individual, keeping prospects/customers satisfied.

Merging and purging data manually can be a time consuming job and errors are likely to be made which is why merge purge software is an essential tool for companies. However, if time is a problem, we can merge and purge your data for you with our data bureau services.

Request a demo today of our merge purge software and see how we can help your with your data quality issues.

Merge Purge Software

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Our Solutions for Merge & Purge

Match | Perfect | Merge | Solution for Dynamics 365

Duplicate detection and multi-record merge software for Dynamics 365 users. More powerful than the out of the box detection.

DQ Match™ – Matching Software for Deduplication

Deduplication cross matching data cleansing software designed to work directly with your database(s) or CRM applications.

DQ Components API™

A set of composable functions providing total flexibility in the way data defects are identified and corrected.

Integrate | Automate | Consolidate | Cleanse

Next generation software for: data migration, application integration, business process automation, data cleansing & business rules execution.

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DQ Global was established almost 20 years ago, with a view to providing companies with the software tools required to deal with the growing problems of managing Data Quality.

Our clients use our powerful data cleansing capabilities for data governance, master data management, data migration and integration projects, business rules automation and single customer view.
Armed with accurate and trusted data they have been able to drive out waste, reduce risk and make better informed business decisions.

Who trusts us with their data?

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