With Data Ladder’s world-class fuzzy matching software, 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.
| Features of the solution | Data Ladder | IBM Quality Stage | SAS Dataflux | In-House Solutions | Comments |
|---|---|---|---|---|---|
| Match Accuracy (Between 40K to 8M record samples) |
96% | 91% | 84% | 65-85%* | Multi-threaded, in-memory, no-SQL processing to optimize for speed and accuracy. Speed is important, because the more match iterations you can run, the more accurate your results will be. |
| Software Speed | Very Fast | Fast | Fast | Slow | A metric for ease of use. Here speed indicates time to first result, not necessarily full cleansing. |
| Time to First Result | 15 Minutes | 2 Months+ | 2 Months+ | 3 Months+ | |
| Purchasing/Licensing Costing | 80 to 95% Below Competition | $370K+ | $220K+ | $250K+ | Includes base license costs. |
Note: in-house implementations have a 10% chance of losing in-house personnel, so over 5 years, half of the in-house implementations lose the core member who ran and understood the matching program.
*Above tests were completed on 15 different product comparisons with university, government, and private companies (80K to 8M records). This includes the effect of false positives.
Research reveals that 94% of businesses admit to having duplicate data, and the majority of these duplicates are non-exact matches and therefore usually remain undetected. Fuzzy name matching software helps you make those connections automatically using sophisticated proprietary matching logic, regardless of spelling errors, unstandardized data, or incomplete information.
Fuzzy Matching is defined as the process of identifying records on two or more datasets that refer to the same entity across various data sources such as databases and websites. Fuzzy name matching software is required when combining data sets that don’t have a common identifier, such as an identification number, or when linking records where exact matches are rare because of misspellings, unstandardized data, or incomplete information. The technique is invaluable when creating a Single Customer View (SCV) or building a strategic foundation for Master Data Management (MDM).
Regular matching techniques won’t be able to detect a match between “Hammer” and “Hamer”, but fuzzy matching software will.
Set a match threshold (0-100%), match on multiple fields/columns, and see the match percentage on each field/column.
Leverage standardization libraries to match variations of first names or nicknames – “Vinny” and “Vinnie”, or “Peggy” and “Margaret”.
Match “Cleaners” and “Cleanrs”, “Folder” and “Foldwer” using phonetic fuzzy matching algorithms like Metaphone 3.
Studies evaluating the top 15 data quality vendors found that ours was consistently the fastest and most accurate fuzzy matching software.
Data Ladder offers pre-populated, fully customizable nickname, address, abbreviation, phone number, and pattern-based libraries.
Determine cross-cultural matches regardless of language or country. All languages in the Unicode standard are supported.
The Quick Data Profile tool finds and fixes data quality issues within the first 5 minutes of setup to improve match quality.
It does a great job with data cleansing making the matching process even more powerful and being able to merge rows with very flexible rules for the final export is extremely helpful.
DataMatch Enterprise is easy to learn and use. It’s easy to review results. Saves us tons of time in manually checking records.
It makes our matching projects in a short amount of time and helps prove ROI to our clients.
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