Fuzzy Matching Software
Quickly and accurately clean data and remove duplicates using world-class fuzzy matching. Best in class data quality suite for data cleansing, standardization, matching, and record merging.
You can visually score matches, assign weights, and group non-exact matches using advanced deterministic and probabilistic matching techniques, further improved with proprietary fuzzy matching algorithms.
Experience best-in-class matching with a solution that beats IBM and SAS in speed, accuracy, and ease-of-use in 15+ independent studies.
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- No credit card required. Fully Functional
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Customer Stories
See what our customers say...
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
Want to know more?
Check out DME resources
Merging Data from Multiple Sources – Challenges and Solutions
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The Truth About Data as a Service (DaaS): Why It All Breaks Without Data Matching
Everyone’s Talking About DaaS, Few Are Ready for It The concept of Data as a Service (DaaS) is having its moment. On paper, it’s easy
Big Data Analytics Is Booming – But Is Your Data Ready for It?
Amazon generates 35% of its revenue from data-powered recommendations. Netflix enjoys an 89% retention rate by personalizing every experience using viewer behavior, preferences, and interaction
The Truth About Data as a Service (DaaS): Why It All Breaks Without Data Matching
Everyone’s Talking About DaaS, Few Are Ready for It The concept of Data as a Service (DaaS) is having its moment. On paper, it’s easy
Big Data Analytics Is Booming – But Is Your Data Ready for It?
Amazon generates 35% of its revenue from data-powered recommendations. Netflix enjoys an 89% retention rate by personalizing every experience using viewer behavior, preferences, and interaction
Data Ethics in the Age of AI: Why Responsible Matching Matters More Than Ever
When AI systems deliver inaccurate or inequitable results, many people immediately assume that something went wrong in the algorithms. Rarely do we look upstream –
