DataMatch Enterprise Server + API
DataMatch Enterprise Server + API is a plug and play system that permits flawed data to be usable. Enabling real-time fuzzy search of your databases quickly and easily, DataMatch Enterprise Server is the world’s best record linkage software.
Get Clean, Stay Clean Solution
DataMatch Enterprise Server + API is a component written by Data Ladder for state of the art fuzzy matching, data formatting, and data cleansing – amongst its most common uses are duplicate prevention, inquiry, deduplication and merge/purge. The Data Match Enterprise API splits and cases names and addresses, generates match keys for phonetic matching, uses probabilistic language models for a more accurate fuzzy match, and grades matching records.
The component provides a compact and efficient solution to the problems of data quality and duplication on any Windows-based system.











High Performance & Scalability
Delivers results quickly regardless of size of database

Real-Time Data Quality Firewall
Match and prevent duplicates and bad data from entering your systems as it is entered

Intuitive Interface
Execute data projects within a matter of days

Robust Matching Technology
Find what you’re looking for with the world’s best matching and deduplication technology

Seamless Integration with Databases
Operates apart from and links to current databases for maximum speed and efficiency as part of the API

Quick Implementation
No advance preparation needed to start
How It Works

So what do you do if there are inconsistencies or variations in your data? Even worse, what if there are different errors in both a database and a search engine? Data Ladder’s DataMatch Enterprise Server + API finds the right data – even with incomplete information. Our algorithms can find the areas of similarity regardless of what fields they’re located in or however the data is aligned.
DataMatch Enterprise Server + API can handle many of the issues that compromise your data systems. Our system is scalable – even with large datasets, the information can be analyzed with lightning fast response times. The result for you? Increased accuracy and less manual work needed. Our software integrates directly with your database, yet functions independently and doesn’t affect any other applications.
Our platform is a robust approach to making imperfect data usable. Our platform can make the right connections with any type of structured data. From spelling errors to redundancies, our tool can work through many of the common issues found in large amounts of data.
As seen in 20 different independent match comparisons, DataMatch Enterprise Server found 5-10% more matches than any competitor or in-house solution.
Match Accuracy
40K Records | 400K Records | 400K to 4M Records | Speed | Purchase / Licensing Costs | |
---|---|---|---|---|---|
Data Ladder | 96% | 91% | 95% | Very Fast | Low |
IBM Quality Stage | 88% | 87% | 91% | Fast | High ($250K Plus) |
SAS DataFlux | 84% | 84% | 81% | Fast | High ($250K Plus) |
Data Ladder | IBM Quality Stage | SADS Data Flux | |
---|---|---|---|
40K Records | 96% | 88% | 84% |
400K Records | 91% | 87% | 84% |
400K to 4M Records | 95% | 91% | 81% |
Speed | Very Fast | Fast | Fast |
Purchase / Licensing Costs | Low | High ($250K Plus) | High ($250K Plus) |
Note the above tests were completed on internal test data (External confirmation in process). Note that these tests were done using our propietary algorithms, no pre processed algorithmic results were used.
API Architecture Diagrams

Have a specific data quality problem in mind?

Overview
There are two fundamental parts to the Data Match Enterprise API:
- Record Indexing
- Record Matching
These can be utilized in different scenarios:
- Data capture incorporating duplicate prevention
- Single data source matching
- Cross data source matching
Match Definitions
Match definition is a set of rules we apply on the fields to apply in the matching process. Match definition for one field consisting of:
Matching type which can be Fuzzy or Exact.
Before doing any of those two (Fuzzy or Exact) we can transform the input to its phonetic equivalent:
– Phonetic
Example: phonetic transformation of words Dayton and Deighton is equal.
If match definition is Fuzzy than we need to apply a value for the:
– Level
It defines the threshold for the comparator. If the results of the comparison are equal to higher than Level, the match would be considered successful.


Matching Scores
Matching score is the average value of all matching scores per individual fields. If any field has a matching level below the level the complete score will be 0.
Explore the Platform
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Ready To Start Preparing Your Data to Match, Clean, and Enrich It?
During your 30-day trial, you can access DataMatch Enterprise risk-free. The software is user-friendly and easy to install – what you see is what you get! However, we recommend a 30 to 60-minute non-obligatory online consultation with one of our subject matter experts to help you get the most out of your free trial.