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
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Merging Data from Multiple Sources – Challenges and Solutions
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Building a case for data quality: What is it and why is it important
According to an IDC study, 30-50% of organizations encounter a gap between their data expectations and reality. A deeper look at this statistic shows that:
Data quality API: Functions, architecture, and benefits
While surveying 1900 data teams, more than 60% cited too many data sources and inconsistent data as the biggest data quality challenge they encounter. But
Building a case for data quality: What is it and why is it important
According to an IDC study, 30-50% of organizations encounter a gap between their data expectations and reality. A deeper look at this statistic shows that:
Data quality API: Functions, architecture, and benefits
While surveying 1900 data teams, more than 60% cited too many data sources and inconsistent data as the biggest data quality challenge they encounter. But
Batch processing versus real-time data quality validation
A recent survey shows that 24% of data teams use tools to find data quality issues, but they are typically left unresolved. This means that