Data Deduplication Software
Identify and remove duplicates in virtually any data source using world-class fuzzy matching logic to enhance productivity and make better decisions with clean data. Reduce redundancy across disparate data sources and build enriched, golden record quickly all within an intuitive, graphical interface.
Our industry-leading data deduplication software helps you find matches within and across data sources with 96% accuracy using proprietary fuzzy, phonetic, and domain-specific techniques to build clean, consistent data in any source and format.
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Customer Stories
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It’s not just the software which works very well for us, but the focus and knowledge that Data Ladder brings to the table
Thanks to Data Ladder we successfully cleaned up and matched our internal sales file with new leads, greatly improving efficiency and sales.
We could not do these reports before. Now, DataMatch has become a main staple in my suite of tools that I work with
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Merging Data from Multiple Sources – Challenges and Solutions
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What Are Entity Graphs and How to Build One You Can Trust
Last Updated on October 8, 2026 An entity graph shows a single match group as a network, with each source record as a node and
What’s New in DataMatch Enterprise: REST API, Docker Deployment, and a Rebuilt Matching Engine
Last Updated on September 7, 2026 DataMatch Enterprise just shipped a REST API, a containerized deployment, and a rebuilt matching engine. In internal testing, the
What Are Entity Graphs and How to Build One You Can Trust
Last Updated on October 8, 2026 An entity graph shows a single match group as a network, with each source record as a node and
What’s New in DataMatch Enterprise: REST API, Docker Deployment, and a Rebuilt Matching Engine
Last Updated on September 7, 2026 DataMatch Enterprise just shipped a REST API, a containerized deployment, and a rebuilt matching engine. In internal testing, the
Build vs. Buy Entity Resolution: What’s the Better Option for Your Team?
Last Updated on August 7, 2026 Entity resolution is the process of identifying which records across one or more systems refer to the same real-world
