What is Data Matching?

Data matching, also known as record linkage, is a data management process that allows you to accurately identify, match, merge and duplicate records across disparate data sources for the availability of complete and up-to-date across the enterprise.

How Can Data Matching Software Help you Grow Your Business?

For a complete, accurate view of enterprise-wide data, data stewards must collaborate and come up with a data governance strategy to unify and match records across information systems and applications that collect customer data.

Data matching software

Execute proprietary and industry-grade match algorithms – based on custom-defined criteria and match confidence levels – for exact, fuzzy, numeric, or phonetic matching, and visually deduplicate or merge records belonging to the same entity.

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Benefits

Why do you need a data matching tool?

Increase operational efficiency

Reduce manual labor, level up data quality, and optimize business processes with automatic data matching technology.

Facilitate any use case

Whether you want to clean mailing lists, detect fraudulent behavior, or match patient records, data matching software can help you out.

Ensure data compliance

Ensure that the records in your databases follow data compliance standards, such as GDPR, HIPAA, CCPA, etc.

Enrich data for deeper insights

Efficiently match organizational data present at different data stores and determine the next best move for your business.

Execute custom data matching

Weigh in the nature of your data and choose the right matching fields, algorithms and confidence levels to attain the best match results.

Reduce computational complexity

Eliminate duplicate records present in databases and free up storage space to attain quick and timely query results.

Features

What DME’s data matching can do for you?

Automatic mapping of data fields

Use DME to intelligently map data fields and reduce the hassle of manually assessing and renaming fields across disparate sources. DME achieves this by creating word clouds of all values in a field, and mapping the ones having the maximum number of common values.

Configurable match definitions and criteria

In DME, you can create multiple match definitions, and each definition can hold multiple criteria. This structure helps you create various logical AND/OR expressions, based on which the data records can be matched. Furthermore, you can assign custom weights to matching fields to ensure prioritized calculation of match scores.

Variety of match algorithms

DME uses the correct algorithms, combining established and hybrid, depending on the nature of your data. You can, of course, fine-tune the setting to emphasize certain types of data matching, for example, exact, fuzzy , numeric, phonetic, or domain-specific matching.

Match scores and confidence levels

DME outputs the match results in terms of scores that indicate the level of match confidence. DME calculates the match score as a numeric value in the range of 0 – 100%, and allows you to set the deciding level that classifies records as a successful match or non-match.

Resolution of false positives and negatives

Rerun match algorithms with varying threshold levels and choose the deciding value that ensures least number of false positive and negatives. Moreover, you can also flag records as duplicates or non-duplicates and correct any misclassified record.

Action steps for match results

DME allows you to utilize the match results for subsequent steps of deduping , merging, and purging data records. You can also use the match results and scores to create survivorship rules or perform advanced data analysis – for example, merging records that show a high level of match confidence, or identify households where records have the same (or similar) residential address.

There’s more

What else do you get out of the box?

Our data matching solution comes with a number of in-built features that facilitate easy, automatic, and cost-effective data matching operations at any time.