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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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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How to improve data quality: Define, design, and deliver
Today, data is no doubt one of the biggest assets of an organization. It is used everywhere – from a company’s day-to-day operations to its
Guide to pattern matching: What it means and how to do it?
Finding patterns is easy in any kind of data-rich environment; that’s what mediocre gamblers do. The key is in determining whether the patterns represent signal
How to improve data quality: Define, design, and deliver
Today, data is no doubt one of the biggest assets of an organization. It is used everywhere – from a company’s day-to-day operations to its
Guide to pattern matching: What it means and how to do it?
Finding patterns is easy in any kind of data-rich environment; that’s what mediocre gamblers do. The key is in determining whether the patterns represent signal
Data standardization guide: Types, benefits, and process
When you pull data from various applications fitted across the enterprise, you expect to receive a consistent definition and format of the same information. But